An executive at a British record company was interested in what his company could do to increase record sales. They looked at record sales (in thousands of albums), advertising budget (in thousands of pounds), airplay (the number of times the record is played on the radio during the week prior to release), the attractiveness of the singer (on a scale from 1-10), and the gender of the singer. Initially, the company just needs to compile descriptive statistics for this data and run some simple analyses.

The data set listed on the next page is a random sample of data from this study.Using R, input the data and answer the following questions:

Note:when you input the data, remember which ones will be used categorically and which will be quantitative.Looking at the data below will help.

1)Create bar graphs OR histograms for the following variables. Write up a brief description of the patterns you see:

a)Gender

b)Attractiveness of singer

2)Create another variable that puts the attractiveness of singer into 3 categories: Ratings of 1-4 are considered Low Attractive, ratings of 5-7 are considered Moderately Attractive and those rated 8-10 are considered Highly Attractive. Create a bar graph for this variable.

3)Obtain the descriptive statistics (mean, median, variance, standard deviation, minimum and maximum) for each of the three ratio level variables. Create histograms for each variable. Describe the shape of the distribution, whether there are any outliers and what the best measure of center and spread are for each variable.

4)Over the past 5 years, the population mean album sales was equal to 185,000, the population mean advertising budget was 640,000, and the population mean airplay was 37. The executive is interested in whether the data he obtained is different from these population means. Run one-sample t-tests on these variables to test this. By hand, create 95% confidence intervals for the population means for all three variables that match those given to you by R. Discuss how to determine significance using confidence intervals.Write up the results, in APA style, for each t-test.Check the text (or the APA template posted on NYU Classes) for the proper format.Look at the data and think about the results - do they seem unusual, are they what you expect?

5)Make sure to RMD your document into a Word or PDF document.