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Step 1 – Select a Database For this project, you must find some sort of publish

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Step 1 – Select a Database
For this project, you must find some sort of published, existing data.
Possible sources include: almanacs, magazine and journal articles, textbooks, web resources, athletic teams, newspapers, reference materials, campus organizations, professors with experimental data, electronic data repositories, the sports pages
.The dataset you select must have at least 25 cases. It also must have at least two categorical variables and at least two quantitative variables. It is very helpful to have a dataset that interests you.
Step 2 – Analyze your Data!See the description below of what analysis should be included. Use technology as needed to automate calculations and graphs.
Step 3 – Write Your ReportInclude all of the following in your report:
Introduction (7 points): Give a reference for your data and describe all relevant variables. Include the source of the dataset.
Analysis of One Quantitative Variable (10 points): For at least one of the quantitative variables, include summary statistics (mean, standard deviation, five number summary) and at least one graphical display. Are there any outliers? Is the distribution symmetric, skewed, or some other shape?
Analysis of One Categorical Variable (8 points): For at least one of the categorical variables, include a frequency table and a relative frequency table.
Analysis of One Relationship between Two Categorical Variables (25 points): Include a two-way table and discuss any relevant proportions. Does there appear to be an association between the two variables? If so, describe it and test it by stating the appropriate null and alternative hypothesis and calculating the test statistic (Hint: use proportions for the categories of interest as the parameters). Use StatKey to calculate the p-value. State your generic conclusion and conclusion in the context of your data.
Analysis of One Relationship between a Categorical Variable and a Quantitative Variable (15 points): Include a side-by-side plot and describe it. Does there appear to be an association between the two variables? If so, describe it. Also, use some summary statistics to compare the groups. Use StatKey to construct a bootstrap distribution for the difference in means using 2 categories of the categorical variable in your data. Use the bootstrap distribution to construct confidence interval (choose your own confidence level) and be sure to interpret your result in the context of your data situation.
Analysis of One Relationship between Two Quantitative Variables (15 points): For at least one pair of quantitative variables, include a scatterplot and discuss it. Give the correlation and comment on the strength of linear association. Pick one of the variables to be a response variable, use the other as an explanatory variable, and fit a regression line. Interpret the slope of the regression line. Use the regression line to make at least one prediction for a point in the dataset and compute the residual.
Conclusion (10 points): Briefly summarize the most interesting features of your data. As you discuss each analysis, be sure to interpret what you are finding in the context of your particular data situation.

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