Question

To study the effects of an advertising campaign at a supply chain, several stores are randomly selected with the following observed before‐ and after‐advertising monthly sales revenues: Store number 1 2 3 4 5 Old sales revenue (mil. $) 6.5 4.8 7.9 6.2 7.1 New sales revenue (mil. $) 7.5 6.3 7.1 7.8 8.9 Let μ₁ and μ₂ be the means of old and new sales revenues, both in millions of dollars per month. (a)[7] At α = 0.05, test H₀: μ₂ ≤ μ₁ versus H₁: μ₂ > μ₁. Sketch the test. Interpret your result. (b)[3] Sketch and find the p‐value of the test. Would you reject H₀ if α = 0.01? Hint: Use 5 decimals. Refer to some Excel lookups: αv 0.990 0.990 0.950 0.950

Answer 1

Answer:

Check the explanation

Step-by-step explanation:

Part a

H0: µ2≤µ1 versus H1: µ2>µ1

(Upper tailed test)

WE will consider differences as (New – Old).

From given data, we have

Dbar = 0.70

SD = 0.70

n = 5

Degrees of freedom = df = n – 1 = 5 – 1 = 4

Test statistic = t = (Dbar - µd) /[SD/sqrt(n)]

t = (0.70 – 0)/[0.70/sqrt(5)]

t = 0.70/ 0.3130

t = 2.2361

Critical value = 2.1318

(by using t-table)

P-value = 0.0445

(by using t-table)

P-value < α = 0.05

So, we reject the null hypothesis

There is sufficient evidence to conclude that the average monthly sales revenue increases after the advertising.

Kindly check the first attached image for the graphical table.

Part b

P-value = 0.0445

α = 0.01

P-value > α = 0.01

So, we do not reject the null hypothesis

There is insufficient evidence to conclude that the average monthly sales revenue increases after the advertising.

Kindly check the second attached image for the graphical table.