Descriptive Statistics and Correlation Analysis

In the Portfolio Project you will conduct a multiple linear regression analysis of crime data from the counties in Florida Download crime data from the counties in Florida.

The dataset consists of five variables:

1. County - Alpha text - name of Florida county - categorical variable measured on the nominal scale.
2. Crime - Numeric - # of crimes per 1000 residents - continuous variable measured on the ratio scale.
3. Income - Numeric - median income per resident expressed in 1000 dollars - continuous variable measured on the ratio scale.
4. HS - Numeric - % of residents 25 years of age or older with at least a high school diploma - continuous variable measured on the ratio scale.
5. Urban - Numeric - % of residents living in an urban area.

For the linear regression analysis, the Crime variable is designated as the outcome or dependent variable. You will use Income, HS, and Urban as the predictor or independent variables. Your analysis should include the following:

Step 1:

• Upload the Florida.csv file into SAS Studio
• Import the CSV file into a SAS dataset.
• Take screenshots to demonstrate successful completion of your work. The screenshot should show your SAS Studio selections and the results you obtained. The screenshot should have the current date and time.

Step 2:

• Conduct descriptive statistics analysis using the Summary Statistics task for the four continuous variables in the data set. The descriptive statistics should include results tables and visual test results. Include the following statistical test results for each continuous variable in the dataset:
  • Mean, median, and standard deviation.
  • Minimum and maximum values
  • Number of observations and missing observations
  • Confidence limits in the mean
  • Skewness
  • Kurtosis
  • Lower quartile
  • Upper quartile
  • Interquartile Range
  • Histogram
  • Box Plot
• Take screenshots to demonstrate successful completion of your work. The screenshot should show your SAS Studio selections and the statistics test results including visual tests you obtained. The screenshot should have the current date and time.

Step 3:

• Multivariate analysis (correlation) among the predictor variables of the data set. The multivariate analysis must include statistics and visual analysis. Include the correlation statistics and a matrix of scatterplots.
• The objective of this step is to ensure the predictor variables are not highly correlated. If so, they violate the independence assumption within the linear regression model.
• Take screenshots to demonstrate successful completion of your work. The screenshot should show your SAS Studio selection and the statistics test results including visual tests you obtained. The screenshot should have the current date and time.

Step 4:

Summarize your work on this assignment as follows:

• Interpret the statistics test results including visual tests you obtained from your work. Interpretation of results should be relevant and accurate.