1. For each of the following variables: major, graduate GPA, and height:
a. Determine whether the variable is categorical or numerical.
b. If the variable is numerical, determine if it is continuous or discrete.
c. Determine the level of measurement.
2. For variable undergrad specialization:
a. Construct a pie chart.
b. Construct a Pareto chart.
c. What conclusions can your reach about the undergrad specialization?
3. For variable anticipated salary in 5 years:
a. Construct a frequency distribution and a percentage distribution that have class intervals with the upper class boundaries 40, 50 and so on.
b. Construct a histogram.
c. Construct a polygon.
d. Construct a cumulative percentage polygon.
e. Around what amount do the anticipated salary values seem to be concentrated?
For variable anticipated salary in 5 years:
1. Compute the mean, median, and mode.
2. Compute first quartile (Q1) and third quartile (Q3) and the interquartile range. List the five-number summary.
3. Construct a box plot.
4. Compute the variance, standard deviation and co-efficient of variation.
5. Write a brief report summarising your conclusions.
For gender and major:
1. Construct a contingency table.
2. Compute all the conditional and marginal probabilities for the table.
3. Given that a graduate's gender is male what is the probability that the graduate has a major "A".
4. What conclusions can you reach about independence of the major and gender variables? Explain your answer using probabilities found above.
1. For variable anticipated salary in 5 years decide whether the data can be described by the normal distribution:
a. Comparing data characteristics to the theoretical one for the normal distribution.
b. Constructing a probability plot.
2. If you select a sample of n = 50, from the normal distribution with µ = 100 and σ = 35, what is a probability that the sample mean will be greater than 80 and less than 120?
3. Suppose that in a sample of n = 36 salary values, the sample mean was 90 and standard deviation 40. Construct a 90% confidence interval estimate for the population mean.