Statistics homework help

Chapter 13
Exercise 1. The following frequency distribution shows the number of times an outcome was
observed from the toss of a die. Based on the frequencies that were observed from 60 tosses of the
die, can it be concluded at the 0.10 level of significance that the die is fair?
Chapter 14
Exercise 2. A random sample of the following two variables was obtained:
a. Calculate the correlation between these two variables.
b. Conduct a test of hypothesis to determine if there exists a correlation between the two
variables in the population. Use a significance level of 0.10.
Exercise 3. Examine the following sample data for the variables 𝑦 and π‘₯:
a. Construct a scatter plot of these data. Describe the relationship between x and y.
b. Calculate the sum of squares error for the following equations:
(1) π‘¦ΰ·œ = 0.8 + 1.60π‘₯, (2) π‘¦ΰ·œ = 1 + 1.50π‘₯, and (3) π‘¦ΰ·œ = 0.7 + 1.60π‘₯.
c. Which of these equations provides the β€œbest” fit of these data? Describe the criterion you used
to determine β€œbest” fit.
d. Determine the regression line that minimizes the sum of squares error.

Statistics homework help

Chapter 13
Exercise 1. The following frequency distribution shows the number of times an outcome was
observed from the toss of a die. Based on the frequencies that were observed from 60 tosses of the
die, can it be concluded at the 0.10 level of significance that the die is fair?
Chapter 14
Exercise 2. A random sample of the following two variables was obtained:
a. Calculate the correlation between these two variables.
b. Conduct a test of hypothesis to determine if there exists a correlation between the two
variables in the population. Use a significance level of 0.10.
Exercise 3. Examine the following sample data for the variables 𝑦 and π‘₯:
a. Construct a scatter plot of these data. Describe the relationship between x and y.
b. Calculate the sum of squares error for the following equations:
(1) π‘¦ΰ·œ = 0.8 + 1.60π‘₯, (2) π‘¦ΰ·œ = 1 + 1.50π‘₯, and (3) π‘¦ΰ·œ = 0.7 + 1.60π‘₯.
c. Which of these equations provides the β€œbest” fit of these data? Describe the criterion you used
to determine β€œbest” fit.
d. Determine the regression line that minimizes the sum of squares error.