Category: Statistics

For your initial Post: Create a linear regression equation in Excel. State what

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For your initial Post:
Create a linear regression equation in Excel. State what

For your initial Post:
Create a linear regression equation in Excel. State what the regression equation is in your post.
Define your input and output variables.
State and interpret the correlation coefficient.
State and interpret the coefficient of determination.
State the range of ages for which this linear regression equation is appropriate.

Unlimited Attempts Allowed For this assignment, you will use a data generator to

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Unlimited Attempts Allowed
For this assignment, you will use a data generator to

Unlimited Attempts Allowed
For this assignment, you will use a data generator tool to generate hypothetical data for the questions you developed.
To generate data using the survey data generator, complete the following:
Open the Survey Data Generator. https://media.capella.edu/CourseMedia/MAT2001/Surv…
The Survey Data Generator will generate responses to the set of six survey questions you previously defined. It knows nothing about the particular subject of your study; it only generates a set of responses to question types that are predefined.
Type the minimum, the maximum, and the expected values for questions 5 and 6 into the Survey Data Generator. (These are values for the quantitative questions from Table 1 of your completed Data Collection Template.) Note that the generator has spaces only for the values for your two quantitative questions.For the top set of boxes, enter the values for question 5.
For the bottom set of boxes, enter the values for question 6.
For each of these questions, you must enter a single number for the minimum, the maximum, and the expected value.
For each of these questions, do not enter commas or other symbols.
Select Download Excel Spreadsheet. An Excel spreadsheet will be created that contains your survey responses.
Keep in mind the following about the Excel data:Excel will have six columns (A–F) and one column for each question (1–6).
Columns A–D represent the responses for questions 1–4 and should only contain 0s and 1s. Columns E and F represent the responses for questions 5–6 and should contain numbers between your minimum and maximum.
Each row will represent the responses from one survey participant. For example, the first row of answers represents the first survey participant’s answers to all six questions. The second row of answers represents the second survey participant’s answers to the questions—and so forth. The number of rows of answers is how many participants completed the survey.
You need to use the Survey Data Generator again if a column contains all the same numbers. There must be variation in these responses for you to statistically analyze the data. Check to see that columns 1 through 4 contain a mix of 0s and 1s and that columns 5 and 6 contain a range of different numbers between your minimum and maximum.
Identify what the 0s and 1s mean in columns A through D. The generator automatically generates 0s and 1s for the responses to your binary questions (1–4), so do not enter anything into the generator for these questions. The tool knows that the only possible responses for these questions are 0 and 1. For example, if you asked: “Are you male of female?” you could assign Male = 0 and Female = 1, or vice versa. For the next project assignment (u07a2), you will analyze the survey responses and will need to assign 0 and 1 to the two possible responses for your binary questions; it is up to you which response to assign 0 and which to assign 1. For this assignment, u05a2, you do not need to submit your assignment of these values—just keep this in mind for the future.
Make sure you have watched the Week 5 Project Video. Your instructor will walk you through the process for completing this assignment.
https://media.capella.edu/coursemedia/mat2001eleme…Instructions
Submit the Excel spreadsheet to your instructor in the Survey Results assignment area. Do not manipulate the results created by the survey generator. No statistical calculations are completed until the next project assignment.
Review the Survey Results rubric and the Statistical Analysis course project description prior to submitting this assignment, to ensure you have met the expectations of the assignment.
Competencies Measured
By successfully completing this assignment , you will demonstrate your proficiency in the following course competencies and rubric criteria:
Competency 4: Solve problems in your personal and professional life by applying statistical procedures.Prepare survey results.
Appropriately format data from a study.

The short assignment and the long assignment should, ideally, both be part of th

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The short assignment and the long assignment should, ideally, both be part of th

The short assignment and the long assignment should, ideally, both be part of the same research project, and you should think of them as being different sections of the same research report.
In the short assignment, you briefly lay the theoretical groundwork for your research project, and identify, assess, and describe the data and variable measures that you will analyse. However, you should NOT undertake any analysis of the relationships between variables, which will be the focus of the long assignment.
As with any research project, you should begin by identifying your research question(s) and then the theory and literature that are relevant to your research question(s). This will enable you to identify the causal relationship between two variables that you are interested in investigating, which you will need to specify. Subsequently, your assessment of the theory and literature can also be used to inform the hypothesis (or hypotheses) about the relationship between the variables that you offer in the long assignment.
You then identify the data that you will analyse. You should also describe and assess the quality of the data and the measures of the variables that you will analyse. In the case of the measures, you should identify any issues with the operationalisation of the variables that you are interested in.
Further, describing your measures includes producing descriptive statistics such as the ones that we cover in the second lecture. You may use figures to graphically present information on your measures, but this is not necessary. For the avoidance of doubt, you should NOT analyse the relationships between any of your measures in the short assignment.
A possible structure for your short assignment is as follows:
Brief introduction
Theory and literature:
Research question and its importance
Review of relevant theory and literature
Identification of causal relationship between two variables of interest
Data and variable measures:
Identification, description and assessment of data
Identification, description and assessment of measures of the key variables in the data
Brief conclusion
Given the space constraints, the short assignment is an exercise in writing succinctly and presenting as much information as possible in a constrained space. You should summarise relevant theory and literature breifly, giving an idea of the key ideas and debates relating to your research project. If you have the sense that a theory or piece of literature is only loosely or tangentially related to the focus of your research, then you do not need to cover it; focus instead on the most relevant and important theories and literature.
Similarly, when identifying, describing and assessing the measures of your variables, you are welcome to focus only on measures of your dependent variable and one key independent variable. You do not need to provide detail on other measures of variables that you might end up including as controls in the analysis that you conduct for the long assignment.
The short assignment is a focused piece of work, designed to give the reader an immediate sense of the key variables that your research project will investigate, and their possible relationship(s), and how they are measured in the data that you will use.
The word limit for the short assignment is 1,000 words and the deadline is Thursday 15 February.

1. Open the excel attached. 2. Sample 50 rows following the instruction in the v

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1. Open the excel attached.
2. Sample 50 rows following the instruction in the v

1. Open the excel attached.
2. Sample 50 rows following the instruction in the video (https://toptipbio.com/random-sampling-excel/) start at the 3 minute mark – using Method 2). You are to sample across all columns and then save the Excel Workbook as your own unique, personal dataset (Urfa Jamil.xlsx)
Select one (1) categorical and two (2) quantitative variables.Visualize and describe the distribution of each variable using appropriate methods in Excel. For each variable, separately provide:one visual (e.g. graph) – remember the principles of good graphing;
appropriate descriptive statistics;
a one-sentence description of the distribution of the variable. (See examples below.)
Spot and describe outliers in the dataset. Do not remove!
Analyze the relationship between the two quantitative variables using the regression options in Excel. Identify which variable is the dependent variable (response) and which variable is the independent variable (explanatory). Provide:
• scatterplot – remember the principles of good graphing;
• appropriate statistics including the line of best fit (regression equation);
• description of the relationship between the two variables that includes the interpretation of correlation, slope and intercept, and the coefficient of determination; and finally a
• recommendation as to whether or not your model should be used for predictions.
Write a two-page Data Report based on your exploration using the following sections:Introduction that briefly states the purpose and contents of the report.
Data section describing the dataset.
Methods section describing the choice of variables, visuals created, summary statistics calculated.
Analysis section that contains the required analyses from 5(a-c).
Conclusion giving the most relevant observations and interesting findings.
The results of a statistical analysis should reinforce common sense
• Is the slope reasonable?
• Does the direction of the slope seem right?
• Always be skeptical and ask yourself if the answer is reasonable
Be Careful
• Don’t fit a straight line to a nonlinear relationship
• Beware of extraordinary points
– Look for y-values that stand off from the linear pattern
– Look for x-values that exert a strong influence
• Don’t extrapolate far beyond the data
• Don’t infer that x causes y just because there is a good linear model for
their relationship
• Don’t choose a model based on R2 alone
• Be sure to get the regression the right way around

1. Open the excel attached. 2. Sample 50 rows following the instruction in the v

Posted on | by Laureen | Leave a Comment on 1. Open the excel attached. 2. Sample 50 rows following the instruction in the v

1. Open the excel attached.
2. Sample 50 rows following the instruction in the v

1. Open the excel attached.
2. Sample 50 rows following the instruction in the video (https://toptipbio.com/random-sampling-excel/) start at the 3 minute mark – using Method 2). You are to sample across all columns and then save the Excel Workbook as your own unique, personal dataset (Urfa Jamil.xlsx)
Select one (1) categorical and two (2) quantitative variables.Visualize and describe the distribution of each variable using appropriate methods in Excel. For each variable, separately provide:one visual (e.g. graph) – remember the principles of good graphing;
appropriate descriptive statistics;
a one-sentence description of the distribution of the variable. (See examples below.)
Spot and describe outliers in the dataset. Do not remove!
Analyze the relationship between the two quantitative variables using the regression options in Excel. Identify which variable is the dependent variable (response) and which variable is the independent variable (explanatory). Provide:
• scatterplot – remember the principles of good graphing;
• appropriate statistics including the line of best fit (regression equation);
• description of the relationship between the two variables that includes the interpretation of correlation, slope and intercept, and the coefficient of determination; and finally a
• recommendation as to whether or not your model should be used for predictions.
Write a two-page Data Report based on your exploration using the following sections:Introduction that briefly states the purpose and contents of the report.
Data section describing the dataset.
Methods section describing the choice of variables, visuals created, summary statistics calculated.
Analysis section that contains the required analyses from 5(a-c).
Conclusion giving the most relevant observations and interesting findings.
The results of a statistical analysis should reinforce common sense
• Is the slope reasonable?
• Does the direction of the slope seem right?
• Always be skeptical and ask yourself if the answer is reasonable
Be Careful
• Don’t fit a straight line to a nonlinear relationship
• Beware of extraordinary points
– Look for y-values that stand off from the linear pattern
– Look for x-values that exert a strong influence
• Don’t extrapolate far beyond the data
• Don’t infer that x causes y just because there is a good linear model for
their relationship
• Don’t choose a model based on R2 alone
• Be sure to get the regression the right way around