Supply and Demand Tug of War Is at the Forefront After a Mixed Week of Data

Data from this week consisted of a series of highs and lows, as the mixture of lingering supply chain issues, rising prices and still-strong consumer demand continues to make its way into economic data. The week began on a positive note, as new home sales increased 14% to a 800K-unit pace last month following existing home sales, which rose 7% last week. Home buying’s second wind combats the notion that growth in the housing market is slowing after over a year of bustling activity. In recent months, much of the pessimism surrounding the housing sector was a result of builders’ inability to get the materials and labor needed to complete homes, much less afford them, as well as the pricing out of many first-time or lower-income home buyers. Some of these concerns should subside as builders are creatively navigating supply constraints. Completed homes rose to a six-month-high, reaching a 207K-unit pace, and price growth subsided to a still-elevated 18.7% year-over-year increase in September, down from 23.3% the prior month. However, with the number of homes put up for sale but not yet started rising to its highest since 2006, supply chain issues still appear to be having an impact on the sector.

The first gain in consumer confidence in three months was another early-week upside surprise. After months of confidence missing expectations, a recharged consumer is welcome news. The increase was due to renewed optimism around both consumers’ present situations and expectations for the future, which bumped the headline four points to 113.8. Consumers’ positive views on the labor market contributed to the rise in confidence, as did the recent decline in COVID cases.

Encouragingly, consumers also expressed a willingness to pack their bags for vacation and hit the stores during the holiday season. Nearly half of consumers (47.6%) responded they were planning to go on vacation in the next six months, the highest proportion since the start of the pandemic. Buying plans for large appliances, vehicles and homes in the next six months all rose as well, signaling that consumers may intend to spend more in the near-future. Until these plans are realized, we know there is an element of hearsay to these estimates, but personal spending data this week also showed signsof robust consumer demand. Spending rose 0.6%in September, despite a 1.0%decline in personal income, and was driven mostly by continued strength in the service sector. In particular, recreation services and food services and accommodations led the gains in September, rising 1.7% and 1.3% over the month, respectively. Although September’s headline growth falls below the 1.4%averaged in the first two quarters, personal spending is already 3% above its pre-pandemic level (see chart). Encouragingly, real spending, which accounts for price increases, also rose for the second consecutive month, its first back-to-back monthly increase since this spring as a result of the acceleration of price growth this summer.

Summarize the sections below

In the second half of the week, we learned that the U.S. economy expanded at a 2.0% annualized rate in the third quarter (see chart), below the consensus expectation for a 2.6% gain. There was evidence of supply chain constraints throughout the underlying data as bottlenecks drove prices higher and made many goods simply unavailable. After two consecutive quarters of inventories being a drag on growth, they added 2.1 points and were the only reason growth did not stagnate. Remarkably, this lift came merely from a slower drawdown in stockpiles. Trade, on the other hand, was a sizable drag on headline GDP growth for the fifth consecutive quarter amid resilient domestic demand, shaving 1.7 points off of top-line growth. This was expected after September’s advance trade data, which showed the deficit widening to -$96.3B. While imports were able to notch a 6.1% gain in Q3, exports fell by 2.5%.

It was broadly expected that real personal consumption expenditures (PCE) would have some fallout while navigating the rocky terrain of the Delta variant and stifled production as labor and material shortages plagued factories’ ability to produce, but the 1.6% increase exceeded expectations. While this would be nothing to scoff at pre-COVID, the 1.6% boost looks tiny compared to the over 12% annualized pace we saw in the two preceding quarters. While services more than pulled its weight in the third quarter, rising at a 7.9% annualized pace, goods spending fell victim to the air pocket that we had been warning about, and sunk 9.2% in Q3. Durables in particular were to blame, as they receded 26.2% in the third quarter. Rising prices also cut into real gains across the board, as the PCE deflator rose at a 5.3% annualized rate in the third quarter. That boosted the year-over-year rate of consumer inflation to 4.4%—the highest in over 30 years. We look for prices to come down over next year, but not fully back to the Fed’s 2% target as expected by policymakers.

Real equipment spending was rather weak during the quarter, with a 3.2% annualized dip due largely to holdups in production. The manufacturing sector has been struggling with rising backlogs and wait times, as there are still bottlenecks at the nation’s largest ports—in recent days, over 70 container ships have been idling in the ports of Los Angeles and Long Beach as they wait to unload their products. In this week’s durable goods release, total unfilled orders rose for the eighth consecutive month in September, while backlogs of core capital goods rose to a record high of $235B. This is consistent with the recent upward march in the ISM supplier deliveries index, as moving product from one place to another has become an expensive and arduous task. 

Assume that students are distributed RANDOMLY in a college hallway. Which research design is used here?

What follows is a true story.

Three researchers, Lindsay Levine, Thomas Bluni, and Sidney Hochman, were interested how people responded to non-verbal communication in the form of personal artifacts, specifically, how people were dressed. In their literature review they found that people were generally more likely to cooperate with or help people who were nicely dressed.

They decided to extend this research to the question of charitable behavior. Their proposition was that better dressed solicitors for charitable causes would get more donations than poorly dressed solicitors.

To test this, they recruited three female high school students as confederates. The confederates each assembled two sets of clothes: for “Preppy” attire they wore neat, pressed, well-coordinated and tailored clothing, and new shoes; for “Messy” attire they wore unpressed, uncoordinated clothing, tee shirts, loose sweaters, and worn, dirty sneakers.

Each confederate was assigned to a different floor of a large college building. They wore one of the outfits as determined by a flip of a coin for each confederate. They each held an official American Cancer Society coin collection can, and were instructed to ask every third student passing them by, “Will you contribute?” After thirty requests the confederates changed into their other suit, returned to their floor, and asked thirty more students “Will you contribute?”

The confederates were told they were helping raise money for the American Cancer Society. They were not told the proposition.

Observers watched the confederates from a discreet location. They recorded the success or failure of each request. A request was considered successful if a) the solicited student donated or b) they reached into their pocket for money, whether they actually donated or not.

This protocol led the researchers to the hypothesis that preppie-dressed confederates would be more likely to get a donation or attempted donation than messily-dressed confederates.

Okay, ready?

1. Assume that students are distributed RANDOMLY in a college hallway. Which research design is used here? (5 points)

2. Why were the confederates not told about the proposition? (2 points)

3. Does the manipulation of attire possess face validity? Why or why not? (2 points)

4. What was conducted as a pretest? (2 points)

Now for the fun part. Sorry, I can’t help myself: mua ha ha ha ha.

Here are the Observed outcomes. The numbers in this table refer to the number of students.

                                                            Dress

                                                Preppie            Hippie             Marginal

                        Yes                       50                    18                    68

Donation

                        No                        40                    72                   112

Marginal                                       90                    90

You will note I have calculated the marginals for you. The experimental protocol has also simplified your life in a mathematical way you will see if you know what you are doing. 🙂

5. What is the Expected value for each cell? (10 points)

6. What is the chi-squared f or the table? You are required to do this by hand. Include an image – I don’t care how you get it – of your work. No image, no credit. (20 points)

7. How many Degrees of Freedom in this test? (2 points)

8. What is the Critical chi-squared for this test assuming alpha = .10? Yes, I said .10. (2 points)

9. Are the results statistically significant or non-significant? (2 points)

10. Is the hypothesis supported or falsified? (3 points)

There are a total of 50 points available for the homework. I promise I will not curve the scores down. Partial credit is available for questions 1, 5, and 6 ONLY.

Find the rejection region appropriate for this test if we are using a significance level of 0.05

Question 1

A consumer product magazine recently ran a story concerning the increasing prices of digital cameras. The story stated that digital camera prices dipped a couple of years ago, but now are beginning to increase in price because of added features. According to the story, the average price of all digital cameras a couple of years ago was $215.00. A random sample of n = 22 cameras was recently taken and entered into a spreadsheet. It was desired to conduct a test to determine if that average price of all digital cameras is now more than $215.00. Find the rejection region appropriate for this test if we are using a significance level of 0.05. Assume camera prices are normally distributed.

Group of answer choices

Reject H0 if t > 1.717

Reject H0 if t > 2.080

Reject H0 if t < -2.080 or t > 2.080

Reject H0 if t > 1.960

Reject H0 if t > 1.721

Question 2

In a sample of 1600 computers, 344 were fournd to contain some form of malware. Find the margin of error for a 90% confidence interval estimating the true proportion of computers with malware.

Group of answer choices

0.0131

0.0169

0.0265

0.0201

0.0239

Question 3

A large electric utility claims that 80 percent of their customers are very satisfied with the service they receive. To test this claim, the local newspaper surveyed 200 customers. The results of the study are shown in the printout below.


   One-Sample Z Test

   Null Hypothesis: p = 0.8
   Alternative Hyp: p ≠ 0.8

                               95% Conf Interval

   Variable      p-hat  SE     Lower    Upper    Z      P
   Satisfaction  0.735  0.028  0.674    0.796    -2.30  0.0214

   Cases Included 200


Based on these findings, can we reject the electric utility’s claim that 80% of their customers are very satisfied? Using the above software output and a 5% significance level, what is the test’s conclusion?

Group of answer choices

H0 is not rejected. There is insufficient evidence to reject the claim that 80 percent of customers are very satisfied with the service they receive.

H0 is rejected. There is sufficient evidence to reject the claim that 80 percent of customers are very satisfied with the service they receive.

H0 is rejected. There is insufficient evidence to reject the claim that 80 percent of customers are very satisfied with the service they receive.

H0 is not rejected. There is sufficient evidence to reject the claim that 80 percent of customers are very satisfied with the service they receive.

Question 4

The Golden Comet is a hybrid chicken that is prized for its high egg production rate and gentle disposition. According to recent studies, the mean rate of egg production for 1-year-old Golden Comets is 5.4 eggs/week.

Sarah has 44 1-year-old hens that are fed exclusively on natural scratch feed: insects, seeds, and plants that the hens obtain as they range freely around the farm. Her hens exhibit a mean egg-laying rate of 5.8 eggs/day.

Sarah wants to determine whether the mean laying rate μ for her hens is higher than the mean rate for all Golden Comets. State the appropriate null and alternate hypotheses.

Group of answer choices

H0μ = 5.4, H1μ > 5.4

H0μ = 5.8, H1μ > 5.8

H0μ > 5.4, H1μ = 5.4

H0μ > 5.8, H1μ = 5.8

Question 5

Express the confidence interval (-1.22, 2.76) calculated for an unknown population mean μ in the form of point estimate ± margin of error.

Group of answer choices

0.77 ± 1.99

1.99 ± 0.77

1.89 ± 0.77

0.77 ± 1.89

0.77 ± 1.79

Question 6

A test of  versus  is performed using a significance level of . The value of the test statistic is .

If the true value of p is 0.35, does the test conclusion result in a Type I error, a Type II error, or a Correct decision?

Group of answer choices

Type II error

Correct decision

Type I error

Question 7

What is the critical value zα/2 for a 75% confidence level?

Group of answer choices

1.25

0.67

2.24

1.15

1.96

Question 8

Estimate the P-value for a test of H0μ = 12 versus H1μ ≠ 12 with test value t = -2.61 and a sample size of 15.

Group of answer choices

0.01< P-value < 0.02

0.025 < P-value < 0.05

0.02 < P-value < 0.05

0.005 < P-value < 0.01

0.01 < P-value < 0.025

Question 9

Historically, 40% of students at a university live on campus. In a new survey conducted to see if the current rate differs from the previous one, 91 out of 250 students randomly surveyed reported that they live on campus. Find the test statistic value for a test of the claim.

Group of answer choices

-1.16

-1.20

-1.18

-1.22

-1.14

Question 10

A machine is used to fill cans with 500 grams of a product. Over time the machine has a tendency to stop short of dispensing a full 500 grams. The machine needs to be serviced when the mass of the product dispensed is significantly lower than 500 grams.

Suppose that the average amount dispensed by the machine for a sample of 50 cans is 498 grams. Is there sufficient evidence that the machine should be serviced? Find the P-value for the test. Assume a population standard deviation of 6 grams.

Group of answer choices

0.0091

0.0273

0.0364

0.0455

0.0182

Question 11

A random sample of 11 patients had an average incubation period for a virus of 5.1 days with a standard deviation of 2.3 days. Construct a 99% confidence interval for the true mean incubation period, μ, of the virus. Assume patient incubation periods are normally distributed.

Group of answer choices

(3.5, 6.7)

(3.7, 6.5)

(2.9, 7.3)

(4.0, 6.2)

(3.3, 6.9)

Question 12

A monthly income investment scheme exists that promises variable monthly returns. A study of 300 months’ returns with this scheme was conducted. The results of the study are shown in the printout below.

   One-Sample Z Test

   Null Hypothesis: μ = 180
   Alternative Hyp: μ > 180

                              99% Conf Interval 

   Variable    Mean    SE     Lower    Upper    Z     P
   Return      190.33  4.518  178.69   201.97   2.29  0.0110

   Cases Included 300


An investor will invest in the scheme only if they are assured an average monthly return greater than $180. Should they invest in this scheme? Using the above software output and α = 0.01, what is the test conclusion?

Group of answer choices

Invest in the scheme. There is sufficient evidence to support the conclusion that the average monthly return is greater than $180.

Do not invest in the scheme. There is sufficient evidence to support the conclusion that the average monthly return is greater than $180.

Do not invest in the scheme. There is insufficient evidence to support the conclusion that the average monthly return is greater than $180.

Invest in the scheme. There is insufficient evidence to support the conclusion that the average monthly return is greater than $180.

Question 13

A study is being conducted to estimate the proportion of students interested in taking a course in a new subject area. How large of a sample is needed in order to be 90% confident that the sample proportion will not differ from the true proportion by more than 2%?

Group of answer choices

1702

241

2401

3404

4802

Question 14

A new filament design is tested to see if lightbulbs using the design last longer than the current bulb’s lifetime of 1430 hours. A sample of 40 bulbs employing the new filament had an average lifetime of 1450 hours. Compute the test statistic value for a hypothesis test of  versus  where μ is the new bulb’s true average lifetime. Assume  hours.

Group of answer choices

1.57

1.96

1.69

1.74

1.83

Question 15

How many flights must be sampled to estimate the true mean delay time for a particular airline if we want 95% confidence that the sample mean is within 5 minutes of the true mean, and the population standard deviation is known to be 20 minutes?

Group of answer choices

27

87

107

44

62

Question 16

Some hesitation about the unthinking use of significance (hypothesis) tests is a sign of statistical maturity. Which one of the following statements regarding significance tests is actually true?

Group of answer choices

An important practical distinction should be made between a P-value of 0.049 and a P-value of 0.051.

Statistical significance is a formal measure of practical importance or signficance.

The null hypothesis can be rejected by chance alone even if the null hypothesis is true.

Failure to reject the null hypothesis is likely to occur if the sample size is too large.

One can legitimately test a hypothesis on the same data that first suggested that hypothesis.

Question 17

The nicotine amounts in milligrams of 8 randomly selected cigarettes of a certain brand are given below. Find a 95% confidence interval for the true mean nicotine content per cigarette for this brand. Assume cigarette nicotine amounts are normally distributed.

3.1     4.5     4.2     6.0     5.1     3.3     5.9     2.5

Group of answer choices

(3.14, 5.51)

(3.57, 5.08)

(3.24, 5.41)

(3.27, 5.38)

(3.42, 5.23)

Question 18

A researcher conducts a study to see if college students get the same amount of sleep as the average adult does, which is 7.25 hours of sleep. A sample of 27 college students shows an average amount of sleep of 6.75 hours with a standard deviation of 1.15 hours. Are college students getting the same amount of sleep as the average adult? Calculate the test statistic value and state its P-value for a test of this conjecture. Assume the population is normally distributed.

Group of answer choices

t = -2.26; 0.02 < P-value < 0.05

t = -2.26; 0.025 < P-value < 0.05

t = -2.26; 0.01 < P-value < 0.025

z = -2.26; P-value = 0.0238

z = -2.26; P-value = 0.0119

Question 19

A random sample of 75 boxes of a certain brand of cereal has a mean weight of  = 17.95 oz. Construct a 99% confidence interval for the mean weight, μ, of all boxes of cereal of this brand. Assume σ = 0.81 oz.

Group of answer choices

17.71 oz. < μ < 18.19 oz.

17.80 oz. < μ < 18.10 oz.

17.69 oz. < μ < 18.21 oz.

17.77 oz. < μ < 18.13 oz.

17.73 oz. < μ < 18.17 oz.

Question 20

In a survey of 229 customers, 68 said they like pepperoni on their pizza. Construct a 95% confidence interval for the true proportion of customers that like pepperoni on their pizza.

Group of answer choices

0.258 < p < 0.336

0.238 < p < 0.356

0.219 < p < 0.375

0.247 < p < 0.347

0.244 < p < 0.350

Show that the distance from downtown to ballpark play important role in increase attendances.

Section 4: Business Analytics Solution (flexible length)

In this section, you will use one or more datasets to show the client organization how you solve the business problem by business analytics approach. You are expected to use at least two data mining techniques you learn from this course (e.g., predictive modeling, classification, association, text mining, etc.) to show the client organization that your solution can be used not only for descriptive and visual analytics, but also for advanced data analytics that can help the organization make better decisions and ultimately improve their performance. You can use Tableau, Excel, or other data visualization tools for descriptive analysis. However, you must use SPSS statistics and SPSS Modeler for the data mining parts. In case that you use any additional programming/scripting languages (e.g., R, python, etc.), discuss with the instructor in advance. The body of your report should contain results of the analysis, some graphs (if applicable), some tables (if applicable), and implications of your business analytics solutions for the client organization. Keep in mind that most of the clients are not business analytics experts. Avoid using too much technical jarg.

What is the Project?

This one section of the Project, I am using cluster analysis to determine that the ballpark location close to city downtown help to increase the attendances. I completed the cluster analysis on the SPSS modeler, and I placed the result on the PowerPoints and the excel sheet.

I need to write one or two pages to analysis this data to show from that the distance from downtown to ballpark play important role in increase attendances. Please using the charts, I provide to complete this section.

I need to provide the distance from downtown to the Ballpark play big factor in attendances number but same team I need to analysis the other factors on the datasheet.

Please use only this cluster analysis data and graphs in your analysis

Explain the importance of your consulting team’s ethics and integrity (establish trustworthiness)

COMPANY BACKGROUND

This section helps to describe the background of your consulting team. NOTE: This is where your consulting team will need to PROVE your credibility. ALL OF THE FOLLOWING SUB-SECTIONS MUST BE INCLUDED IN THIS SECTION, UNLESS INDICATED.

Introduction (Paragraph 1)–No sub-section needed

This is a few sentences describing the important components of this section. Preparing the reader for what will be included.

Company Values (Separate Sub-Section with Multiple Paragraphs)

When did this consulting team originate? Why? What teamwork or leadership principles do the consulting team value? (Look for ideas in Chapter 1, 3, 10)
Indicate the consulting team’s experience and competence in this professional field or working with professional organizations or other companies in recommending effective communication strategies?
Explain the importance of your consulting team’s ethics and integrity (establish trustworthiness). (Look for ideas in Chapter 1, 3, 10)
Internal and External Communications (Separate Sub-Section with Multiple Paragraphs)

Indicate how your consulting team “communicates” with their employees, clients, vendors, etc. (tone, motivation, frequency, etc.). Procedures for decision making, team work, etc.
Describe the overall importance of “listening” and “nonverbal communication” your consulting team values.

DIRECTIONS FOR STATEMENT OF NEED:

STATEMENT OF NEED—page number

This section is the first and most important part. Developing this section sets the stage for all other aspects of the proposal. This section indicates in paragraph format WHY your selected department/organization needs your consulting team’s expertise based on the areas of focus. Your team will need to provide some “EVIDENCE” in the form(s) of statistics, testimony, comparison and/or analogies, recent news in the media, success of other departments/organizations, etc. You will need to find or “make up” this evidence by actually researching in the library, internet, or other organizations. I PROVIDED SOME THEORETICAL REASONS IN THE “OVERVIEW.”

ALL OF THE FOLLOWING SUB-SECTIONS MUST BE INCLUDED IN THIS SECTION (you can re-name the sections, but the “intent” of the questions should be addressed),

Introduction (Paragraph)

This is a few sentences describing the important components of this section. Preparing the reader for what will be included.

History of Organization (Separate Sub-Section with Multiple Paragraphs)

What is the history of the department/organization’s image?
Who makes up their internal audience (employees, students, college administration, other departments/organizations, etc.)
Who makes up their external audience (customers, clients, suppliers, government, competitors, etc.)
What types of rewards or benefits does/can your target market(s) expect from this organization/department?
Organizational Needs (Separate Sub-Section with Multiple Paragraphs)

Who will benefit from your team’s proposed recommendations? (consider all stakeholders)
Why does this department/organization “matter” matter to their stakeholders?
Why might your recommendations be necessary or desired by the various stakeholders?
Why haven’t these areas of focus been addressed sufficiently in the past? What are other competing departments/organizations doing to address these areas of focus? Are they effective?
Conclusion (Last Paragraph)

End the section by indicating “In closing,” “In summary,” “In conclusion,” etc. along with a few sentences highlighting the section and the fact that your consulting firm has done sufficient research to address their communication concerns.

DRAFT: INTERNAL & EXTERNAL COMMUNICATION

Even though only one team member is responsible for this section, ALL team members should read it prior to submission to ensure it has all the correct content, formatting, grammar, punctuation, etc.

To the team member responsible for the INTERNAL/EXTERNAL COMMUNICATION section. Please read the directions below carefully.

Finally, use the template provided in this section. By doing so, your section and all the other sections will be formatted consistently. In order to use the template, type over the words on the template with the content you are putting in this section. Remove the box at the end of the template after you have read it.

DIRECTIONS FOR INTERNAL/EXTERNAL COMMUNICATION:

INTERNAL/EXTERNAL COMMUNICATIONS—page number

This section helps to describe the existing communication strategies along with the department/ organization’s SWOT Analysis related to their communication strategies. You will need to include:

Introduction (Paragraph 1)

This is a few sentences describing the important components of this section. Preparing the reader for what will be included.

Current Communications (Separate Sub-Section with Multiple Paragraphs)

This sub-section will be several paragraphs and a chart or graphic describing visually either internal, external, or both forms of communication—break into paragraphs or sub-sections for internal and external so they are separated and not together. Remember, you need to describe the chart/graphic first in writing then refer the reader to the chart, table, or graphic like authors do in various textbooks.)

INTERNAL COMMUNICATION

Indicate in the narrative how the department/organization “communicates” in writing, orally, electronically, via internet, through U.S. Mail, etc. to their “internal” stakeholders—(department–employees & administration) or (organization–executive officers & UWG administration).

EXTERNAL COMMUNICATION

Indicate in the narrative how the department/organization “communicates” in writing, orally, electronically, via internet, through U.S. Mail, etc. to their “external” stakeholders—(department—students, community, businesses)—(organization—members, non-members, alumni, community).

**MANDATORY** THIS CHART CAN BE BOTH INTERNAL & EXTERNAL: You MUST create a chart (or table) describing these current communications and indicate how effective these communications are to the stakeholders (members, vendors, companies, executive board, etc.) –this may be in the form of a feature/benefit chart, frequency table, frequency timeline, etc.

SWOT Analysis (Separate Sub-Section with Multiple Paragraphs)

This sub-section will be several paragraphs focusing on the SWOT topics so they are easy to understand; you must narratively describe in writing then refer the readers to the mandatory chart—look at your textbooks to see how author’s refer readers to figures, tables, and/or illustrations.)

Prepare a S-W-O-T Analysis (Strengths, Weaknesses, Opportunities, Threats) by describing it first in a paragraph and then inserting a chart/figure of the SWOT Analysis. You will need to refer the reader to the chart in this section. Therefore, you will need to label the chart. YOU MUST CREATE A CHART OR FIGURE FOR THIS PART OF THE SECTION. Again, prior to placing the chart into the document, you must briefly describe the chart and indicate to the reader to refer to the chart/figure, which will be below the narrative.

Comparative Analysis (Separate Sub-Sections with Multiple Paragraphs)

You will need to compare your department/organization to another either comparable or competitive department/organization possibly on another campus or a different department/organization on our campus that may have similar goals and objectives. This section allows readers to see the similarities and differences related to their communication strategies compared to other “similar” organizations/departments. You may want to ask your contact person to indicate what other universities are similar to theirs or if there is another department/organization on our campus that maybe comparable

Conclusion (Last Paragraph)

End the section by indicating “In closing,” “In summary,” “In conclusion,” etc. along with a few sentences highlighting the section and some of the important facts presented in this section.

EXECUTIVE SUMMARY

Even though only one team member is responsible for this section, ALL team members should read it prior to submission to ensure it has all the correct content, formatting, grammar, punctuation, etc.

To the team member responsible for the EXECUTIVE SUMMARY section. Please read the directions below carefully. Be sure you include all the required information…use the template provided below.

Check out the example provided–do NOT copy or you will lose 50 points. Double-check with your team members on what to include (you can look at your team members sections so you can include a summary from each major section).

DIRECTIONS FOR EXECUTIVE SUMMARY SECTION:

EXECUTIVE SUMMARY—page number (this is the FIRST PAGE)

THIS IS COMPLETED LAST. The executive summary is the LAST thing you do with the exception of the table of contents and possibly the letter of transmittal. The executive summary is the summary of your entire proposal. You will provide the reader with a snapshot of what is to follow. This statement will contain all of the key information and can be considered “a sales document” designed to convince the reader that this proposal should be considered for support. You will need to include in a narrative format:

Introduction of the Proposal (Paragraph 1)

Statement of Need (Paragraph 2)—This paragraph briefly describes the need for your consulting team to make recommendations to improve the three areas of focus; in other words, the threats and weaknesses facing the organization. (Refer to the Statement of Need Section)

Recommendations (Paragraph 3)—This paragraph should include a brief description of how your consulting team’s recommendations will benefit your department/organization’s target audience(s). You will indicate the department/organization’s areas of weakness or threats and how your consulting team will HELP turn them into strengths and opportunities. (See Recommendations Section)

Conclusion/Your Team (Paragraph 4)—This paragraph is the final, concluding paragraph of this section. Indicate how your consulting team has the best, well-researched recommendations that will assist the department/organization’s areas of focus (strong image, increased membership or involvement, and events/activities to increase exposure and communications). You will need to “pump up” your consulting team’s image by indicating your team’s reputation, previous consulting experience, etc., which helps to establish your team’s credibility. (Refer to the Company Background Section).

DIRECTIONS FOR THE CONCLUSION

Even though only one team member is responsible for this section, ALL team members should read it prior to submission to ensure it has all the correct content, formatting, grammar, punctuation, etc. See example.

To the team member responsible for the CONCLUSION section. Please read the directions below carefully. Be sure you include all the required information…you will need to set this up with three paragraphs and a complimentary close with all your team members’ names.

Double-check with your team members on what to include (you’ll want to take the highlights of the proposal and include them to be persuasive). You may even want to offer an incentive in your consulting fees, etc. to make it more attractive to do business with your company.

DIRECTIONS FOR CONCLUSION SECTION:

CONCLUSION—page number

Your team will need to summarize the main points of this recommendations proposal. This is very similar to what you will write in your executive summary except from the understanding that your audience has ALREADY read this proposal. Whereas, the executive summary, you must write it with the understanding that the audience has NOT read the proposal. Include:

Introduction (Paragraph 1)

This is a few sentences indicating the end of the proposal and how the department/organization should hire your consulting company to implement the proposed recommendations.

Body (Paragraph 2 – ?)

This needs to focus on highlighting the recommendations of the proposal and the benefits. Remember to be PERSUASIVE so that your proposal is approved. Once again…this section MUST be PERSUASIVE (A-I-D-A).

Conclusion (Last Paragraph)

End the section by indicating “In closing,” “In summary,” “In conclusion,” etc. along with a few sentences highlighting the entire proposal and your consulting team’s desire to implement these recommendations.

Build a simple logistic regression model using “Survival” as the response variable and “Fares” as the predicting variable

You will use the Titanic data to answer the following questions

Q1. Build a simple logistic regression model using “Survival” as the response variable and “Fares” as the predicting variable.  

          a. Provide the Maximum Likelihood Estimation Table here. 

          b. Write down the equation of the fitted logistic regression model here.

c. Comment if the estimated coefficient associated with the variable “Fares” is statistically significant.  Justify your answer.

d. Interpret the estimated coefficient associated with the variable “Fares”. 

Do passengers who pay higher fares have a higher chance of survival?

Q2. Build a logistic regression model using “Survival” as the response variable and “Age” and “Class” as the predicting variables.

          a. Fit a logistic regression model to the data and provide the Maximum Likelihood Estimation Table. 

          b. How many design variables do you need for modeling the variable “Class”?

          c. Which class is used as the reference class in your logistic regression model?

          d. Write down the equation of the fitted logistic regression model if a passenger is from the first class.

          e. If a passenger is from the first class, what is his/her odds of survival

Why did Mathilde Loisel decide to borrow this particular necklace?

1. Why did Mathilde Loisel decide to borrow this particular necklace? In what ways does her choice imply the nature of her values?

2. Why didn’t Mathilde simply go to her friend and confess that she had lost the necklace, asking for time to raise the funds needed to replace it? What would have happened if she had? Alternatively, why didn’t Mathilde change her mind and confess during the ten-year interval?

3. How has Mathilde changed during these ten years? Does she in any sense grow or benefit from the experience? Do we admire her more? Explain.

4. What do you imagine will happen after the surprising revelation about the jewels? Would Mathilde seek some kind of compensation?

In your own words, how are a one-sample z-test and one-sample chi-square test similar? What do they have in common?

In your own words, how are a one-sample z-test and one-sample chi-square test different? How would we decide which test is correct to use?

Math problems

FiveThirtyEight is a political polling organization that uses statistics to understand the world around us. They are interested in understanding how eligible voters will cast their ballot for the upcoming midterm elections. As a starting point, they want to know whether there is an equal number of voters that identify with the three types of political parties (i.e., Democrat, Independent, and Republican). Based on a series of polls conducted over the past two weeks with 10,000 individuals who are eligible and planning to vote, they found that 3,126 voters identified with Democrats, 4,124 identified with Independents, and 2,750 identified with Republicans.

Did FiveThirtyEight find an equal number of voters in the three types of political parties, or were some parties more popular than others? Use the conventional critical alpha value of .05. In your answer, you should report the chi-square value (χ2), the critical chi-square value that needs to be exceeded, and make a decision about the hypothesis.

Over the past three semesters, I asked students in my two classes (n = 132) about their vacation preferences. Excluding the category “Other”—which no one selected—there were six options to choose from: Mountains/wilderness, Beach, Cruise, Explore a new city, Road trip, and A trip abroad. The two most frequently selected options were “A trip abroad” (51 times) and “Beach” (45 times). “Explore a new city” (15 times), “Cruise” (8 times), “Mountains/wilderness” (7 times), and “Road trip” (6 times) were also selected.

Assuming that these vacations are equally preferred in the general population, do the preferences of students in my classes differ from the population? Use the conventional critical alpha value of .05. In your answer, you should report the chi-square value (χ2), the critical chi-square value that needs to be exceeded, and make a decision about the hypothesis. 

SPSS problem

For this problem, you will need to download the datafile posted on Blackboard titled, “Class Survey F21_Vacation.sav”.

First, run a Frequency analysis on the variable “Vacation” and include a bar chart. Copy and paste (or take a screenshot) of the bar chart that SPSS produces.

Second, perform a one-sample chi-square test on the “Vacation” data. Copy and paste (or take a screenshot) of the output that SPSS produces.

Third, report your findings in APA format. This should include the chi-square value (χ2), degrees of freedom (df), p-value, and a decision about the hypothesis.

Determine the coefficient of determination and interpret its meaning in the context of wind speed and atmospheric pressure – Project-1-Intensity of Hurricanes

Introduction: Hurricanes are natural events that bring destruction in many different ways. They are tropical storms with high wind speeds that can unleash gallons of rain. The high winds may spawn tornadoes and the torrential rains may cause floods and landslides. The destructive nature of hurricanes after making landfall is very devastating, to the extent that houses are wiped off the map and the floods deposit debris of damaged homes. Sometimes human lives are lost through this destructive natural event. As residents in our various communities, it is very important to have some level of knowledge about hurricanes and familiarize ourselves with the best practices and safe measures in the event of a hurricane. A hurricane is an intense cyclonic storm that develops over the warm oceans of the tropics. It usually begins as a tropical disturbance and turns into a tropical depression when the speed of the wind attains 61 kilometers per hour (km/h) or equivalently 38 miles per hour (mph) at the storm center. When the sustained wind speed attains 63 km/h (or 39 mph) the tropical depression becomes a tropical storm. The tropical storm is classified as hurricane when the sustained wind speed reaches 119 km/h (or 74 mph). Using the Saffir-Simpson scale the hurricane is categorized a rating of 1 to 5. In the northern Indian Ocean, the tropical storm is known as a cyclone and in the western Pacific Ocean it is referred to as a typhoon [1]. You can learn about Hurricanes and Tropical Storms at http://www.physicalgeography.net/fundamentals/7u.html

We wish to determine how sustained wind speed in a hurricane is related to the surface pressure of the storm. The goal of this project is to consider the relationship between wind speed and pressure within a hurricane and, to develop a model that describes this relationship. Please use the dataset on maximum sustained wind speeds measured (mph) and pressures (mb) within hurricanes for the period 2000-2005. Using either SPSS or Excel for statistical analysis of this data set, please answer the following questions.

  1. Identify the response and explanatory variables. Construct a scatter plot for this data set. What kind of relationship appears to exist, if any, between the two variables? Describe the pattern, direction and the strength of association between the two variables.
  2. Determine the linear correlation coefficient. Does the value support your observation in exercise 1?
  3. Is the linear correlation coefficient statistically significant at the 5% level? Explain. What does this tell you about the existence of a linear relationship between these two variables?
  4. Develop a least squares regression model for the two variables. Graph it along with the scatter plot.
  5. Interpret the slope of the least squares’ regression model in the context of wind speed and atmospheric pressure.
  6. Determine the coefficient of determination and interpret its meaning in the context of wind speed and atmospheric pressure.
  7. Use the least squares regression model to estimate the maximum sustained wind speed in a hurricane when the pressure reading is 950 mb.
  8. In 2000 and 2004, hurricanes DEBBY and JEANNE recorded maximum wind speeds of 75 mph and 127 mph, respectively. However, their corresponding pressure readings remain unknown. Use your regression model to predict these pressure readings. Be sure to include appropriate units!

What does it mean to say that a relationship between two variables is spurious?

INSTRUCTIONS

Answer the questions below to the best of your ability. Type your responses in the space provided below each question.

Explain your answers thoroughly and precisely to demonstrate command of the material.

MATERIALS YOU NEED

  you will need access to Stata and the bitdata.dta file with associated codebook. Note that all statistical analysis must be done using Stata. You will see the appropriate variable names in the exam questions.

I. Short Answer

1.  Imagine that you wanted to research the role of greed in whether individuals are likely to be prejudiced towards minority social groups in the United States. In a paragraph, explain how you might conduct either an experiment or an observational study of this research question. In your answer, briefly explain how you would set-up the experiment or observational study. In addition, spend most of your answer explaining the specific strengths and weaknesses of your approach (experiment or observational study) to the research question. Remember to include some of the issues we read about or discussed on this topic this semester, but apply them directly to your specific research approach.

II. Reading and Critically Thinking

Answer the two questions below based on this short article.

Access to Nature Trails Helps Combat Childhood Obesity, Research Shows

A new study might have found a solution to the growing problem of childhood obesity. The researchers found that counties with more non-motorized nature trails and forest lands have higher levels of youth activity and lower youth obesity, while counties with more nature preserves have lower activity levels.

“More non-motorized nature trails available for use in a particular county lead to an increase in the physical activity rates as well as lower youth obesity rates,” Sonja Wilhelm Stanis, an associate professor of recreation and tourism in the Missouri College of Agriculture said in a press statement. This was in contrast to counties with more nature preserves, which showed decreased levels of physical activity among youth, and parklands, which did not show any relationship with obesity levels and physical activity of youth. Overall, this research shows how local policymakers can impact the health of their youth through land-use decisions.”

For the study, researchers analyzed data from every county in Minnesota. They compared youth activity rates and youth obesity rates to the amount of public non-motorized nature trails, motorized nature trails, nature preserves, parklands and forest land available. The researchers also found that though public land was associated with higher activity rates, there was no association between parklands and activity levels or obesity rates.

2a.  What is (one) of the central causal claim of the article above? Be sure to identify clearly the independent (IV) and dependent (DV) variables.

2b. To what degree is the causal claim you identified above justified based on the evidence presented? Explain your answer with specific reference to the criteria/hurdles for causality that we learned this semester.

III. Multiple Choice

Select the one correct answer for the questions below.

3. ___ What does it mean to say that a relationship between two variables is spurious?

  1. The relationship is so complicated that research into the relationship is futile.
  2. The relationship that seems to be true in a bivariate examination is not, in fact, the true relationship.
  3. The relationship is causal.
  4. The relationship is not scientifically interesting.

4. ___ Imagine you want to conduct a bivariate test of significance. Your dependent variable is measured as a continuous variable, and your independent variable is measured as a binary independent variable. Assuming you do not want to recode the variables, which test do you conduct?

  1. Tabular analysis with chi-squared test of significance.
  2. Pearson’s r with a t-statistic.
  3. Difference of means with a t-test.
  4. Flux capacitor with a warp drive test.

5. ___ Which of the following accurately describes content validity for measuring a concept?

  1. Degree to which the measure is related to other measures that the theory requires them to be related to.
  2. Degree to which a measure contains all of the critical elements, that, as a group, define the concept we wish to measure.
  3. Extent to which applying the same measurement rules to the same case or observation will produce identical results.
  4. None of the above.

6. ___ Which of the following accurately describes a categorical variable?

  1. A one-unit increase in the variable value always means the same thing.
  2. Different values mean different things.
  3. The values are ordered from least to greatest.
  4. Both b and c are accurate.

7. ___ The central limit theorem states and implies:

  1. There is no difference between a random sample distribution of values (regardless of sample size) and the true population values.
  2. A sampling distribution for a variable is normally distributed only if the underlying population is distributed normally for that variable.
  3. Sampling distributions are often observed in real life.
  4. If one were to collect an infinite number of random samples and plot the resulting sample means, those sample means would be distributed normally around the true population mean.

IV. Interpreting Quantitative Research

A researcher hypothesizes that for individuals, a higher level of education is related to his or her support for open, international trade. Based on a survey of 150 people, she finds the following frequencies:

Table 1: Surveyed Relationship between Education and Support for Free Trade as Frequency

 Level of education 
Attitude on free tradeLowHighTotal
Support402565
Oppose602585
Total10050150

8a.  Is there any evidence that education is related to support for free trade? Explain.

8b. What is the appropriate statistical test for evaluating hypotheses about the relationship between these variables in the population?

8c. A researcher conducts a statistical test to evaluate this bivariate relationship. The test yields a p-value of 0.077. What specifically does that p-value score indicate? How do you interpret that in relationship to the proposed hypothesis?

V. Applied Quantitative Research and STATA

Use the bitdata.dta dataset and codebook for questions 9 and 10. Paste any Stata code you use to answer these questions at the end of this exam sheet.

9a. What is the unit of analysis in these data?

9b. Is the level of FDI inflows more heterogeneous (ie more variable) in host states (fdi_host) or home states (fdi_home)? Cite relevant statistics to justify your answer.

9c. Using an appropriate visual and two or three sentences, describe the data on government spending as a share of GDP (min_govexp).  Be sure to cite the most appropriate summary statistics for this variable.

[paste appropriate visual here]

[keep scrolling for final questions]

The variable fdi_home records FDI outflows (% GDP). The variable month_count records the number of months to ratify the BIT. minpolity and log_gapgdppc record the minimum democracy score and the gap between signees in per capita GDP respectively. comcol records whether the countries share a common colonial heritage.

H0: There is no relationship between FDI outflows (%GDP) and months to ratification of the BIT.

HA: An increase in FDI outflows is associated with a decrease in the number of months to ratify the BIT.

10a. (25 pts) Use linear regression to estimate two models. First, estimate the effect of FDI outflows on the time to ratification (Model 1 below). Then estimate the same relationship conditional on colonial heritage, level of democracy and relative wealth (Model 2). Use the estimates to fill in the table below (round to the 2nd decimal place).

 DV: Months to ratification
 Model 1Model 2
Independent VariablesEstSEEstSE
FDI outflows (%GDP)    
Democracy score    
Relative GDP per capita    
Common colonial tie    
Constant    
Observations  
R-squared  

OLS estimates with standard errors. * p < 0.05, ** p < 0.01, *** p < 0.001

10b.  Interpret the results of the bivariate estimate (Model 1). Be sure to explain the estimate itself and interpret its significance. [Bonus points if you can also explain the results in plain language based on the actual units of the dependent variable.]

10c.  Interpret the effect of FDI outflows in Model 2. Again, present the estimate and interpret the result of the significance test.

10d. What are some potential reasons that the multivariate estimate is different from the bivariate estimate? Which model is a “better fit” (more of the variation in the outcome is explained) and how do you know?

REPLICATION FILE: paste below the Stata commands you used to complete the exam.