Listed below are amounts of court income and salaries paid to the town justices. All amounts are in thousands of dollars. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using alphaαequals=0.050.05. Is there sufficient evidence to conclude that there is a linear correlation between court incomes and justice salaries? Based on the results, does it appear that justices might profit by levying larger fines? Court Income 66.0 406.0 1567.0 1131.0 271.0 250.0 112.0 153.0 30.0 Justice Salary 31 42 93 58 45 61 25 26 17a. What are the null and alternative hypotheses?b. Construct a scatterplot.

a) Null hypothesis:

Alternative hypothesis:

b) The scatter plot is on the figure attached.

c)  

Since the p value is lower than the significance level we have enough evidence to reject the null hypothesis at 5% of significance, and we can conclude that the correlation coefficient is significant.

Step-by-step explanation:

Previous concepts

Pearson correlation coefficient(r), "measures a linear dependence between two variables (x and y). Its a parametric correlation test because it depends to the distribution of the data. And other assumption is that the variables x and y needs to follow a normal distribution".

The t distribution (Student’s t-distribution) is a "probability distribution that is used to estimate population parameters when the sample size is small (n<30) or when the population variance is unknown".  

The shape of the t distribution is determined by its degrees of freedom and when the degrees of freedom increase the t distirbution becomes a normal distribution approximately.  

Solution to the problem

In order to calculate the correlation coefficient we can use this formula:  

Let X the Court Income and Y= Justice Salary, for this case we have that:

On this case we got that r =0.874

Part a

Null hypothesis:

Alternative hypothesis:

Part b

The scatter plot is on the figure attached.

Part c

In order to test a hypothesis related to the correlation coefficient we need to use the following statistic:

Where n represent the sample size and the statistic t follows a t distribution with n-2 degrees of freedom:

On this case our value of n = 9 and the statistic is given by:

And the degrees of freedom are given by df=9-2=7

And the p value for this case since we have a bilateral test is given by:

Since the p value is lower than the significance level we have enough evidence to reject the null hypothesis at 5% of significance, and we can conclude that the correlation coefficient is significant.

first one is a: renaming a fraction. second one is c: de-c

step-by-step explanation:

my explanation is that these were the answers on edg : )