Greetings,

Could someone please help with those R programming exercises?

This is your second exercise with real data. This time, instead of a bank of test scores, we will use the 2014 American Community Survey. These data are maintained by the US Census Bureau and are designed to show how communities are changing.

Through asking questions of a sample of the population, it produces national data on more than 35 categories of information, such as education, income, housing, and employment.

you will need to load and activate the ggplot2 package. (I urge you to do the DataCamp exercise first!). For this deliverable, you should provide the following:

1. What are the elements in your data (including the categories and data types)?

2. Please provide the output from the following functions: str(); nrow(); ncol()

3. Make a Histogram of the HSDegree variable using the ggplot2 package.

a. Set a bin size for the Histogram.

b. Include a Title and appropriate X/Y axis labels on your Histogram Plot.

4. Answer the following questions based on the Histogram produced:

a. Based on what you see in this histogram, is the data distribution unimodal?

b. Is it approximately symmetrical?

c. Is it approximately bell-shaped?

d. Is it approximately normal?

e. If not normal, is the distribution skewed? If so, in which direction?

f. Include a normal curve to the Histogram that you plotted.

g. Explain whether a normal distribution can accurately be used as a model for this data.

5. Make a Probability Plot of the HSDegree variable.

6. Answer the following questions based on the Probability Plot:

a. Based on what you see in this probability plot, is the distribution approximately normal? Explain how you know.

b. If not normal, is the distribution skewed? If so, in which direction? Explain how you know.

7. Now that you have looked at this data visually for normality, you will now quantify normality with numbers using the stat.desc() function. Include a screen capture of the results produced.

8. In several sentences provide an explanation of the result produced for skew, kurtosis, and z-scores. In addition, explain how a change in the sample size may change your explanation?

there is alot of data that wont fit in this box nor can i attach it. so here is some of the data.

Thank you