Listed below are the budgets​ (in millions of​ dollars) and the gross receipts​ (in millions of​ dollars) for randomly selected movies. Construct a​ scatterplot, find the value of the linear correlation coefficient​ r, and find the​ P-value using alphaequals0.05. Is there sufficient evidence to conclude that there is a linear correlation between budgets and gross​ receipts? Do the results change if the actual budgets listed are ​$65 comma 000 comma 000​, ​$89 comma 000 comma 000​, ​$51 comma 000 comma 000​, and so​ on? Budget​ (x) 65 89 51 35 204 98 85

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Question :

Listed below are the budgets (in millions of dollars) and the gross receipts (in millions of dollars) for randomly selected movies. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using alpha = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between budgets and gross receipts? Do the results change if the actual budgets listed are $61,000,000, $92,000,000, $48,000,000, and so onBudget(x) 61 92 48 36 135 58 93Gross(y) 69 62 53 58 627 144 42

a. What are the null and alternative hypotheses?i) H_0: rho = 0, H_1: rho < 0

ii) H_0: rho = 0, H_1: rho notequalto 0

iii) H_0: rho notequalto 0, H_1: rho = 0

iv) H_0: rho = 0, H_1: rho > 0

b. Construct a scatterplot. Choose the correct graph below.

c. The linear correlation coefficient r is.

d. The test statistic t is.

e. The P-value is.

Pvalue > α ; Hence, we fail to reject the null.

Step-by-step explanation:

When testing for correlation :

Correlation Coefficient r is always between - 1 and 1. The alternative is always the opposite of the null. To claim that correlation exists, the r will not be equal to 0, because 0 means no correlation.

1.)

H_0: rho = 0,

H_1: rho notequalto 0

2.)

Given the data :

Budget(x) : 61 92 48 36 135 58 93

Gross(y) : 69 62 53 58 627 144 42

Scatter plot is attached below

3.) The linear correlation Coefficient as obtained using technology is 0.751 ; which depicts a strong positive correlation

4.)

Test statistic :

T = r / √(1 - r²) / (n - 2)

r² = 0.751² = 0.564

T = 0. 751 / √(1 - 0.564) / (7 - 2)

T = 0.751 / 0.2952964

T = 2.543

E.)

Using the Value from Tscore calculator :

Pvalue(2.543, 5) ; two tailed

Pvalue = 0.0517

At α = 0.05;

Pvalue > α ; Hence, we fail to reject the null. there is no sufficient evidence to conclude that there is a linear correlation between budgets and gross receipts.

1.0

step-by-step explanation:

10000

step-by-step explanation: divide by 2,