# Introduction

Give an introduction and background information about the broader field of study that provides context for the data set.  State the objective for your analysis of the data (including but not limited to: what knowledge or new information anticipate gaining from analyzing the data, what broader body of knowledge the analysis contributes to, and why you are interested in the topic).

# Section 1: Data set overview and preparation

## 1.1: Data set overview

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## 1.2: Data set summary

State the purpose for which the data were collected, when the data were collected, how the data were collected. On whom or on what were the data collected. The number of observations and number of variables in the originaldata set.

## 1.3: Data preparation methods

State the variables and number of observations you used in your analysis and explain your selections. Explain how observations with missing values were handled. Explain any coding schemes you created or variables you created. If your data do not contain an ordinal variable, create one and explain the importance of the progression of the levels.

## 1.4: Table of variable definitions (see HWs 1 & 2) 1.5: SAS Code for Data Import and Preparation

# Section 2: Posing Statistical Questions

A statistical question is a question for which you need data to answer. You will state three statistical questions to analyze for the project. For each question you pose, make sure it relates to the broader goal of your report using the variables in your data set.

 For each situation, write a statistical question for which you need your data set to answer. Problem Situation Your Question 1 The nature of the linear relationship between two continuous variables. 2 A comparative analysis of the appropriate measures of center and spread among groups formed by stratifying a quantitative variable by the categories of a qualitative variable. 3 The nature of the association between two qualitative variables.

# Section 3: Univariate descriptive statistics and visualizations

Use only the variables stated in your questions from Section 2.

## 3.1: Qualitative variables

For each qualitative variable: a) provide a table containing the frequency, relative frequency, cumulative frequency, and totals, b) generate a bar chart and a pie chart, and c) at least two insightful, interesting, or revealing relative frequencies in the context of the variable.

3.1.1: SAS Code

Your code must include a macro program for Parts A and B. A title or caption needs to be added above the table or below the image when the object is inserted to MS Word. ## 3.2: Quantitative variables

For each quantitative variable: a) provide a table of descriptive statistics, b) generate a box plot and a histogram, c) identify the shape of the distribution, and d) comment on the most appropriate measure of central tendency, the most appropriate measure of dispersion and interpret the associated values in the context of the variable.

### 3.2.1: SAS Code Your code must include a macro program for Parts A and B. A title or caption needs to be added above the table or below the image when the object is inserted to MS Word.

## 3.3: Ordinal variable

For your ordinal variable: a) provide an ordered table containing the frequency, relative frequency, cumulative frequency, and totals, b) generate a pie chart and an ordered bar chart [you do not need to repeat this part if it was done in Section 3.1. Move on to the next prompt].

Discuss the distribution the variable and whether the order of the categories is a factor in what you observe. 3.3.1: SAS Code

# Section 4: Multivariate descriptive statistics and visualizations

## 4.1: Analysis of the linear relationship between (your response variable) and (your explanatory variable).

Provide a seed and draw an SRS where the sample size is equal to 10% of your data observations (round up if you get a decimal). Generate a scatter plot with least squares regression line overlaid. Discuss the form, direction and strength of the relationship between the variables (make sure to include an assessment of the correlation and interpretations of the slope). Make one prediction for the response variable using a value of the explanatory variable of your choosing. Interpret the prediction in the context of the relationship. 4.1.1: SAS Code

## 4.2: A comparative analysis of (your qualitative variable) by (your quantitative variable) groups.

Provide the following: a) a table of the descriptive statistics for each group, b) a side by side box-whiskers plot, c) the 95% confidence interval for the mean of each group and interpretation in context, d) pairwise comparison of the confidence intervals with comments on pairs that are statistical different and explanation of how this difference was determined. 4.2.1: SAS Code

## 4.3: Analysis of the association between (your 1stqualitative variable) and (your 2nd qualitative variable).

Provide the following: a) a frequency table with margin totals, b) a relative frequency table with margin totals, c) a row frequencies table, d) a column frequencies table, e) at least one interpretation of an insightful, interesting, or revealing frequencies in the context of the variables for eachtable, and f) a 100% stacked bar chart of the row frequencies. 4.3.1: SAS Code

# Section 5: Conclusion

Summarize your results from Section 4 from a client based perspective. Discuss how your findings tie back to your analysis objective, and comment on whether (or how) you have met the objective. Using your findings, comment on what you have learned (both from the findings and coding).  Propose a brief plan for future study of your broad topic, and describe ways in which your data set can be used for other statistical methods to possibly support your future study.

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