Compute the pearsons correlation coefficient between the


Individual Assignment

Compile your answers in one Microsoft Word document. Copy and paste all figures from Excel. No late submissions will be allowed.

Question 1 -

You are provided with data on garbage generation per household (all data is in pounds). The Environmental Protection Agency claims that the U.S. generated 251 million tons of trash in 2012.

a. Compute summary statistics (mean, median, mode, standard deviation) for the variables of Household Size (HHSIZE) and paper waste (PAPER).

Provide descriptions of the distributions based on the summary statistics. Address skewness in your description.

b. Generate a scatterplot with clearly labeled axes for Household size and paper waste.  Put paper waste on the Y axis.

c. Compute the correlation between Household size and paper wasteand make an interpretation.  Refer to both the strength and direction of the correlation in your interpretation.

d. Also interpret the correlation as a coefficient of determination (r-squared).

Question 2 -

Refer to the data set Cars. 

a. Generate a scatterplot between the two variables WEIGHT (pounds per car) and HIGHWAY (miles per gallon on the highway).

b. Compute the Pearson's correlation coefficient between the two variables.

c. Provide an interpretation of the correlation obtained. Refer to both the strength and direction of the correlation in your interpretation.

d. Also interpret the correlation in terms of r-squared (coefficient of determination).

e. Comment on this hypothetical statement:  "A strong, negative correlation between the weight of a car and miles per gallon indicates that heavier cars cause mpg to fall."

Question 3 -

Using the Health data in the excel file, conduct a regression to predict the pulse rate using the age of the individuals in the data set.  Show the results of the regression.

a. What is the value of the intercept a?

b. What is the value of the slope b?

c. What is the predicted pulse rate for a 48 year old individual?

d. Interpret the value of the R-squared for the regression model.

e. What other variable would you add to the equation as an independent variable to strengthen its predictive power? Explain?  

Question 4 -

Using data provided from theUS Statewide Crime data set:

a. Construct a scatterplot using Excel or any software (SPSS or Minitab) between the variables "murder rate" and "poverty." Provide an appropriate title for the chart as well as labels for both axes.

b. There seems to be a problem caused by the presence of an outlier. Identify the outlier and delete it (simply erase its value, do not replace with zero).

  • Show the new (second) scatterplot.
  • Describe the pattern that emerges. What might this relationship imply?

c. Compute the correlation coefficient between the two variables and interpret this correlation. Refer to both the strength and direction of the correlation in your interpretation. Also interpret the correlation in terms of r-squared (coefficient of determination).

d. Conduct a regression to predict murder rate from poverty (when the observation for DC is removed from the data set) and interpret the results.

e. What is the predicted value for a state with a poverty rate of 13.4?

f. Interpret the value of the R-squared for the regression model.

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