Category: Statistics

What is the absolute risk reduction for the primary composite end point when com

What is the absolute risk reduction for the primary composite end point when comparing alirocumatb to placebo? Provide your answer in decimal format with three decimal places (eg 0.007, 0.070, 0.700)
We conducted a multicenter, randomized, double-blind, placebo-controlled trial involving 18,924 patiernts who had an
acute coronary syndrome 1 to 12 months earier. Patients were randomly assigned to receive alirocumab subcutaneously
ta dose of 75 mg (9462 patients) or matching placebo (9462 patients) every 2 weeks.
RESULTS:
A composite primary end-point event occurred in 1207 patients in the alirocumab group and in 1,858 patients in the
placebo group. A total of 334 patients (3,5%) in the alirocumab group and 392 patients (4.1%) in the placebo group died
(hazard ratio, 0.85; 95% C1, 0.73 to 098) The incidence of adverse events was similar in the two groups, with the
exception of local injection-site reactions (3.8% in the alirocumab group vs, 2.1% in the placebo group).

Steps to Complete the Week 7 Lab
Step 2: Consider the use of confidence interval

Steps to Complete the Week 7 Lab
Step 2: Consider the use of confidence intervals in health sciences with these articles as inspiration and insights.
Step 3: Using the data you collected for the Week 5 Lab (heights of 10 different people that you work with plus the 10 heights provided by your instructor), discuss your method of collection for the values that you are using in your study (systematic, convenience, cluster, stratified, simple random). What are some faults with this type of data collection? What other types of data collection could you have used, and how might this have affected your study?
Step 4: Now use the Week 6 Spreadsheet to help you with calculations for the following questions/statements.
a) Give a point estimate (mean) for the average height of all people at the place where you work. Start by putting the 20 heights you are working with into the blue Data column of the spreadsheet. What is your point estimate, and what does this mean?
b) Find a 95% confidence interval for the true mean height of all the people at your place of work. What is the interval? [see screenshot below]
c) Give a practical interpretation of the interval you found in part b, and explain carefully what the output means. (For example, you might say, “I am 95% confident that the true mean height of all of the people in my company is between 64 inches and 68 inches”).
d) Post a screenshot of your work from the t value Confidence Interval for µ from the Confidence Interval tab on the Week 6 Excel spreadsheet
Step 5: Now, change your confidence level to 99% for the same data, and post a screenshot of this table, as well.
Step 6: Compare the margins of error from the two screenshots. Would the margin of error be larger or smaller for the 99% CI? Explain your reasoning.
Step 7: Save the Week 7 Lab document with your answers and include your name in the title.

Use SPSS to open the gss.sav dataset and calculate the 95% and 99% percent confi

Use SPSS to open the gss.sav dataset and calculate the 95% and 99% percent confidence interval (CI) for the variable of hrs1[number of hours worked last week]. Interpret the results by applying different confidence intervals. Mention what have you noticed while applying 95% versus 99% CI. Report the result using APA format.

I have attached the problem below. You may have to download G power which is a f

I have attached the problem below. You may have to download G power which is a free software to complete the problems.

Re/App 6 – Discrete Probability Distributions
The data attached is from observat

Re/App 6 – Discrete Probability Distributions
The data attached is from observations of a supermarket “self-checkout” line at random times of day for 25 selected days, for a total of 75 observations. A data value of 1 means there was 1 person in line, a data value of 2 means there were 2 people in line, etc.
In a microsoft word document answer the following questions about the data (data is attached as a file):
(REQUIRED) Answer the following questions about the data:.
(a) What type of data is this? That is, is it: Qualitative Nominal, Qualitative Ordinal, Quantitative Discrete, or Quantitative Continuous data?
(b) Explain WHY you say it is that type. (2 points total for Question 1)
What is the probability P(x > 2)? Express the probability as a decimal, rounded to three places. (2 points)
Find P(x is no more than 12). Express the probability as a decimal, rounded to three places. (2 points)
Does the probability in Question 3 indicate that it was an unusual event? Look up the concept of an unusual event in the textbook, if necessary, before answering! Explain your answer in a full sentence. Be sure you are specific about the value of the probability in Question 3 in comparison to the criterion for an unusual event. (2 points)
In your opinion, does the store need more checkout lanes? Cite specific probabilities from your distribution to justify your written answer; do not just answer yes/no. (2 points)

In Module 9 of this course, you will produce a brief research document about the

In Module 9 of this course, you will produce a brief research document about the subject of your data collection and analysis.
The resources that you will use include the Hunt Library and/or the following databases in order to gather data that you can analyze for your own hypothesis test. Review these websites and their respective databases at this time for familiarity.
Download RSCH 665 Decision Tree for Statistical Tests (DOCX) I have attached below along with my research along the way
Access the following websites to see what kinds of data are available:
Runway Safety Statistics/FAA (Links to an external site.)Links to an external site.
Aviation Accident Database and Synopses/NTSB (Links to an external site.)Links to an external site.
FAA Aviation Safety Information Analysis and Sharing (ASIAS) (Links to an external site.)
Accident and Incident Data/FAA (Links to an external site.)
Airline On-time Statistics and Delay Causes/Bureau of Transportation Statistics (Links to an external site.)Links to an external site.
Data and Statistics for Airport Program/FAA (Links to an external site.)Links to an external site.
Airlines and Airports/Bureau of Transportation Statistics (Links to an external site.)
General Aviation Statistics/AOPA (Links to an external site.)Links to an external site.
Statistical Databook and Industry Outlook/GAMA (Links to an external site.)
Historical Chart Gallery of Market Indexes/Stock Charts (Links to an external site.)Links to an external site.
Injuries, Illnesses, and Fatalities/Bureau of Labor Statistics (Links to an external site.)Links to an external site.
Data and Statistics/OSHA (Links to an external site.)Links to an external site.
Data Sources/Health and Safety Executive (Links to an external site.)Links to an external site.
Web-based Injury Statistics Query and Reporting System (WISQARS)/CDC (Links to an external site.)Links to an external site.
Research and Data/NHTSALinks to an external site.
National Institute for Occupational Safety and Health Data and Statistics Gateway/CDCLinks to an external site.
This should just be a brief research document. I have attached the document for my research and topic. Also I will post helpful videos you can watch to help decide what would be the best statical test used for the research

Please re-write the Discussion and Conclusion (it is highlighted in yellow). It

Please re-write the Discussion and Conclusion (it is highlighted in yellow). It was written before for only one of the articles when it was supposed to be a discussion and conclusion for the ENTIRE paper. Length requirement is no more than two paragraphs.

From the attachment, I answered most of it and got it right but just had 2 quest

From the attachment, I answered most of it and got it right but just had 2 questions remaining that needs to be answered. Everything in green is correct.
Requirements: Please answer attached question

These hands-on practice assignments will familiarize you with JASP, a statistica

These hands-on practice assignments will familiarize you with JASP, a statistical software package.
You will practice each of the types of analyses discussed in class. For each practice assignment, you
will conduct a set of analyses on a real dataset and report the results of these analyses in APA format.
DISTRIBUTIONS AND DESCRIPTIVES
You will use the dataset titled JASP Data – Personality, Risk, Gambling.
(a) Visualize the distributions of at least two variables;
(b) Visualize the distributions of at least two variables split by a categorical variable (e.g.,
conscientiousness by gender)
(c) Report a table of descriiptive statistics (mean, median, mode, variance, std. deviation)
(d) Report a table of descriiptive statistics (mean, median, mode, variance, std. deviation) split by a
categorical variable (e.g., gender)
Submission requirements:
• Please submit a single .jasp file containing your analyses and submit to Dropbox

Choose either topic 1 or topic 2 for your initial post. Respond to either for yo

Choose either topic 1 or topic 2 for your initial post. Respond to either for your peer reply post.
Topic 1:
One goal of statistics is to identify relations among variables. What happens to one variable as another variable changes? Does a change in one variable cause a change in another variable? These questions can lead to powerful methods of predicting future values through linear regression.

It is important to note the true meaning and scope of correlation, which is the nature of the relation between two variables. Correlation does not allow us to say that there is any causal link between the two variables. In other words, we cannot say that one variable causes another; however, it is not uncommon to see such use in the news media. An example is shown below.
Here we see that, at least visually, there appears to be a relation between the divorce rate in Maine and the per capita consumption of margarine. Does this data imply that all married couples in Maine should immediately stop using margarine to stave off divorce? Common sense tells us that is probably not true.

This is an example of a spurious correlation in which there appears to be a relation between the divorce rate and margarine consumption, but it is not a causal link.

The appearance of such a relation could merely be due to coincidence or perhaps another unseen factor.
What is one instance where you have seen correlation misinterpreted as causation? Please describe. This serves as your initial post to the discussion (if you choose topic 1) and is due by 11:59 p.m. EST on Saturday.

-OR-

Topic 2:
Linear regression is used to predict the value of one variable from another variable. Since it is based on correlation, it cannot provide causation. In addition, the strength of the relationship between the two variables affects the ability to predict one variable from the other variable; that is, the stronger the relationship between the two variables, the better the ability to do prediction.

For example, given this data on literacy and undernourishment, we can create a scatter plot which shows that there seems to be a relationship between the variables.
The graph implies that as literacy (x) increases, the percentage of people who are undernourished (y) decreases.

We can calculate a best-fit line equation and use this to predict that the undernourishment rate we would expect in a country with a percentage literacy rate of 87% would be y = (-0.5539)(87)+55.621 or about 7.43 percent.

What is one instance where you think linear regression would be useful to you in your workplace or chosen major? Please describe why and how it would be used. This serves as your initial post to the discussion (if you choose topic 2) and is due by 11:59 p.m. EST on Saturday.

At least one substantive peer reply post is due by 11:59 p.m. EST on Tuesday.