2. Using the MM207 Student Data Set:
a) Select a continuous variable that you suspect would not follow a normal distribution.
b) Create a graph for the variable you have selected to show its distribution.
c) Explain why these data might not be normally distributed.
d) Select a second continuous variable that you believe would approximate a normal distribution
e) Create a graph to show its distribution.
f) Explain why these data might be normally distributed.
What have you selected?
a) To select a continuous variable that may not follow a normal distribution, we can examine variables that are not symmetrical or have outliers. One possible variable in the MM207 Student Data Set that may not follow a normal distribution is "Age."
b) To create a graph to show the distribution of the "Age" variable, you can use a histogram. The horizontal axis represents the age ranges, while the vertical axis represents the frequency or count of individuals in each age range.
c) The data for the "Age" variable may not follow a normal distribution due to several reasons. First, age is often constrained within a certain range (e.g., minimum and maximum age limits), which can result in a skewed distribution. Additionally, the data might not be normally distributed because age distribution can vary depending on the population being studied. For example, if the data set is limited to a particular age group, such as college students, it may not represent the general population's age distribution.
d) To select a continuous variable that may approximate a normal distribution in the MM207 Student Data Set, we can consider variables that are expected to have a symmetrical distribution without significant outliers. One possible variable that may approximate a normal distribution is "Height."
e) To create a graph showing the distribution of the "Height" variable, you can use a histogram or a density plot. The horizontal axis represents different height intervals, while the vertical axis represents the frequency or density of individuals falling within each interval.
f) The data for the "Height" variable may be normally distributed due to several reasons. First, human height tends to follow a bell-shaped or roughly symmetrical distribution in large populations. Additionally, height is not generally subject to strict minimum and maximum limits like age, allowing for more variability in the distribution. As a result, the "Height" variable is likely to approximate a normal distribution in the MM207 Student Data Set.