代写ECON 83a Statistics for Economic Analysis Summer 2023 Problem Set 1代做留学生Matlab程序
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Statistics for Economic Analysis
Summer 2023
Problem Set 1
For all calculations, please provide the formula used and show each step in your answer (please don’t just provide a numeric result). R commands should also be included in the same pdf/word file.
Due date: July 16th 2024 11:59PM EST
1. Use the following information regarding a sample of several students:
a. How many elements are in the above data set?
b. How many variables are in this data set?
c. How many observations are in this data set?
d. Which variables are categorical and which are quantitative variables?
e. What measurement scale is used for each variable?
2. Below you are given the examination scores of 20 students.
52 99 92 86 84
63 72 76 95 88
92 58 65 79 80
90 75 74 56 99
a. Construct a frequency distribution for this data. Let the first class be 50-59. Remember that each class should have the same width.
b. Construct a cumulative frequency distribution.
c. Construct a relative frequency distribution.
d. Construct a cumulative relative frequency distribution.
3. A survey of 400 college seniors resulted in the following cross-tabulation regard- ing their undergraduate major and whether or not they plan to go to graduate school.
a. Are a majority of the seniors in the survey planning to attend graduate school?
b. Which discipline constitutes the majority of the individuals in the survey?
c. Compute row percentages and comment on the relationship between the students’ undergraduate major and their intention of attending graduate school.
d. Compute the column percentages and comment on the relationship between the students’ intention of going to graduate school and their undergraduate major.
4. The following data show the yearly salaries of a random sample of Worcester residents.
For the above sample, determine the following measures (give your answer in dollars):
a. The mean, median, and mode of yearly salary.
b. The 20th, 40th, 60th and 80th percentile.
5. The following table shows the yearly salaries of football coaches in some state- supported universities. Calculate the following measures.
a. Recalculate the mean yearly salary.
b. Recalculate the range.
c. Recalculate the variance.
d. Recalculate the standard deviation.
e. Recalculate the coefficient of variation.
6. The following data represent the daily demand (y in thousands of units) and the unit price (x in dollars) for a product.
a. Compute and interpret the sample covariance for the above data.
b. Compute and interpret the sample correlation coefficient.
R practice
Open this data set in R Studio. Importantly, this data set does not include any information about the two most recent laureates of this award – Paul Milgrom and Robert B. Wilson – who received the Prize in 2020. Find the appropriate bio- graphical information about Milgrom and Wilson (Wikipedia is OK), and update the dataset. (In other words, you should add two new observations to the original data set.) Then, create a new variable, called Age, which records an individual’s age at which he or she received the award.
a. Who was the youngest individual – as measured at the time of the award – to receive the Nobel Memorial Prize? How old was he or she at that time?
b. Who was the oldest individual – as measured at the time of the award – to receive the Nobel Memorial Prize? How old was he or she at that time?
c. Calculate the mean age at the award. (You should use a command called mean.)
d. Calculate the median age at the award. (You should use a command called median.)
e. Calculate the quartiles of age at the award. (You should use a command called quantile, also selecting appropriate options.)
f. Calculate the 10th percentile of age at the award. (Again, you should use quantile, also selecting appropriate options.)
g. Calculate the 90th percentile of age at the award. (Again, you should use quantile, also selecting appropriate options.)
h. Calculate the range of age at the award. (Use commands called min and max.)
i. Calculate the interquartile range of age at the award. (Use – twice – a command called quantile, also selecting appropriate options.)
j. Calculate the standard deviation of age at the award. (Use a command called sd.)
k. Calculate the covariance of YOA and Age. (Use a command called cov.)
l. Calculate the correlation coefficient of YOA and Age. (Use a command called cor.)
m. Briefly comment on the relationship between these two variables.