Data Exercise #2 This data exercise is similar to data exercise 1 but it is for

Data Exercise #2
This data exercise is similar to data exercise 1 but it is for multiple linear regression. You need
at least three independent variables and at least 50 observations. You can use the same data
set as you did for data exercise #1(I will upload a file with data exercise 1 so that you can see the data you might wanna use and the example). However, you may not use data that is pre-packaged from a
textbook or a computer program or exactly from a publication.
(1) Provide at least one histogram. If you are using the same data set as you did for data
exercise 1, do the histogram for a different variable. Comment if the histogram is
skewed or symmetric.
(2) For a different variable create a box plot. Same deal as in (1) if you are using the same
data set from exercise 1 the box plot needs to be for a different variable. Comment if
the data are skewed or symmetric
(3) Provide a table of summary statistics including the mean, median, standard deviation,
minimum and maximum for all of your variables. DO NOT provide the table from excel’s
or R’s pre packaged function for summary statistics. You can use that function but then
you need to delete the statistics that do not pertain to this class and format it so that it
looks better.
(4) Create a different scatter plot with the dependent variable on the y axis and EACH of the
independent variables on the x axis. Comment if there is a positive or negative
relationship between the two variables and if there is a strong or weak linear
relationship for each scatter plot.
(5) Provide the correlation coefficient between ALL of the variables. Which of the
independent variables are most highly correlated to the dependent variable? Which of
the two independent variables are most correlated with each other?
(6) Run a multiple linear regression and provide the output. This can be done in Excel or R.
State what the R-squared is and what it means. Explain what each of the slope
coefficients mean. Which variables are statistically significant at a 5% level?
Template
Histogram:
Graph here
The variable _____ is skewed (symmetric) because _______.
Box Plot:
Graph here
The variable _____ is skewed (symmetric) because _______.
Summary Statistics:
Table of summary statistics here with both the dependent and independent variables.
Scatter Plot for EACH independent variable against the dependent variable.
Graphs here
These variables _____ and ______ are positively (negatively) related because _____ and the
linear relationship appears to be strong (weak). Do this for EACH independent variable.
Correlation Coefficients:
Statistics here
The dependent variable, ____, and the independent variable, ____ , have the strongest
correlation. These two independent variables _____ and _______ have are most correlated.
Multiple Linear Regression:
Put the Excel or R output here.
The R-squared is ____ and it means _______.
Explain what each of the slope coefficients mean.
These independent variables are statistically significant at a 5% significance level because _______.