In this assignment, you should solve four questions, where you will be asked to calculate a linear correlation coefficient and determine whether there is a linear correlation between the two given variables.

Solve the following:
1. Listed below are baseball team statistics consisting of the proportions of wins and the result of this difference: Difference (number of runs scored) - (number of runs allowed). The statistics are from a recent year, and the teams are NY?Yankees, Toronto, Boston, Cleveland, Texas, Houston, San Francisco, and Kansas City.
Difference
163
55
-5
88
51
16
-214
Wins
0.599
0.537
0.531
0.481
0.494
0.506
0.383
a. Construct a scatter plot, find the value of the linear correlation coefficient r, and find the critical values of r from Table A-6 using ? = 0.05.
b. Is there sufficient evidence to conclude that there is a linear correlation between the proportion of wins and the above difference?

2. One classic application of correlation involves the association between the temperature and the number of times a cricket chirps in a minute. Listed below are the numbers of chirps in 1 min and the corresponding temperatures in °F:
Chirps in 1 min
882
1188
1104
864
1200
1032
960
900
Temperature (°F)
69.7
93.3
84.3
76.3
88.6
82.6
71.6
79.6
a. Construct a scatter plot, find the value of the linear correlation coefficient r, and find the critical values of r from Table A-6 using ? = 0.05.
b. Is there a linear correlation between the number of chirps

Given: The paired sample data of the age of mothers and the weight of their children result in a linearcorrelation coefficient very close to 0.
Conclusion: Older mothers tend to have heavier children.
Describe the error in the stated conclusion.
A. A linearcorrelation coefficient very close to 0 implies that there is a

See the attached file for full problem description.
In Display the data in a scatter plot. Then find the sample correlation coefficient r. Determine whether there is a positive linearcorrelation, a negative linearcorrelation, or no linearcorrelation between the variables. What can you conclude?
The annual per capita sug

A study was conducted with alpha = 0.05 to determine if there is a significant linearcorrelation between the number of credit hours earned at the time of taking statistics 101 and the grade in the course. Eight pairs of data were collected.
The linearcorrelation coefficient is y = 0.6777
Pick the correct answer
a. T

Given the following ordered data pairs (x, y), compute the value of the linearcorrelation coefficient r: (2,6) (3,0) (5,15) (5,5) (10,2).
Give the value to 3 significant digits.

Describe the error in the stated conclusion.
Given: There is a linearcorrelation between annual personal income and years of education.
Conclusion: More education causes a person's income to rise.
Choose the correct answer below.
A. the error in the stated conclusion is that if there is no linearcorrelation, there

3) Display the data in scatter plot. Calculate the linearcorrelation coefficient. Use the scatterplot to make a conclusion about
the type of correlation. x: 0 1 2 3 4
y: 0.5 3 2 4 3.5
find the correlation coefficient.
Choose the statement suggested by the scatter plot and the correlation coef

Find the correlation coefficient between X and Y. Is there a weak or strong, positive or negative linearcorrelation between X and Y?
x -5 -3 4 1 -1 -2 0 2 3 -4
y =10 =8 9 1 =2 =6 =1 3 6 =8
Show all work.

Suppose that, for a sample of pairs of observations from two variables, the linearcorrelation coefficient, r, is positive. Does this result necessarily imply that the variables are positively linearly correlated? Explain