Question

this question needs to be done using minitab18 and if you could put the steps for that program that would be amazing :)

Columns Show Navigation Gallery Toolbox Zoom Help rtArt Grap 1. Two groups of painters working for the same company decided to split into two groups A and B. They, both, completed the same number of identical rooms by applying two coats of matte enamel paints Group A painters completed their task by painting each room one wall at a time, whereas Group B painters completed their task by painting all the walls of a room simultaneously. The two groups recorded the number of hours it took to complete each room and recorded their time for the first 12 rooms as shown in the table below A 14 10 4 4 5 19 9 10 10 12 (a) Use Minitab to create side by side normality plots by performing the following operations. Graph - Probablility plot - Single OK. Select Group A and Group B as graph variables Select Multiple Graphs and choose in separate panels of the same graph, and click OK and paste them below. State, violated if you think that the condition of normality has been 121 Normul .. 95% CI Group A Group B 6 Pages: 1 of 5 Words: 0 of 809 e TRK 21 Lr MacBook Pro Columns Show Navigation Gallery Toolbox Zoom Help Quick-Ta SmartArt Graphics Wo 2:34S6910 112 13 14 15 16 12 (b) Use the calculator in Minitab to find the difference between Group A and Group B. Store this difference in another column and copy it in the table shown below. See me if you need help with this GroupA- 141101 4 417 511-9 101 201 i 0112 Group B 16 1076105 23 711 24 12 13 Difference (e) Test, using a 1% level of significance, to see if the method used by group A is less time consuming than Group B. State the appropriate hypotheses. Copy and paste the Minitab output showing the null and alternate hypotheses, test statistics and P-value of this calculation. [21 Pages: 2 of 5 Words 0 of 770 21 Due: March 19, 2019 in class Stat 106 HW 3-A (d) State your conclusion and show the P-value and the critical value on the bell shaped curve shown below. 121 ges2 ot 5 Words 0 of 770 e TRK MacBook Pro

Answer 1

(a) The steps are written in the question.

Step 1: Click GRAPH and then Click probability plot.

Step 2: Select multiple graphs and then check the dialog box stating "separating panels of the same graph". Click OK.

Step 3: On the variables dialog box select Group A and Group B. click OK.

Probability Plot of GROUP A, GROUP B Normal -95% CI 10 GROUP B GROUPA GROUP A Mean 1033 StDev 5.280 12 0.395 P-Value 0314 95 95 GROUP B Mean 12 StDev 6.223 ← 70 입601 a 40 70 0.585 P-Value 0.101 50- 50- LI 3TI 30- 30- 20 10 20

And you will get these graphs.

(b) For this part, firstly label the third column as Differences.

Step 1: Click CALC in the toolbar then click CALCULATOR.

Step 2: A dialog box appears asking you the specifications. Now for the first specification that is store result in one variable: select the labelled third column differences.

Step 3: The formula for this would be Group A - Group B which are feeded in C1 and C2(on my worksheet) So Type C1-C2 for the formula. Click OK.

l Minitab- Untitled - Worksheet 1 **] File Edit Data Calc Stat Graph Editor Tools Window Help Assistant C3 C4 C5 C6 C1 GROUP A GROUP B Differences 14 16 10 10 10 19 23 10 20 10 12 24 12 13 10 12 13 15

(c) Step 1: Click STAT on the toolbar. Then click BASIC STATISTICS and then click TWO SAMPLE T-TEST.

Step 2: A dialog box appears, Firstly select each sample is in its own column. Select Group A for sample 1 and Group B for sample 2.

Step 3: Click Options and then change the confidence level to be 99.0 (as level of significance is 1%). Let hypothesized difference be 0.0 (As we have to calculate group A<Group B).So. select the alternative hypothesis to be Difference < Hypothesized difference. Click OK.

Step 4: Click ok.

This is your output.

Two-Sample T-Test and CI: GROUP A, GROUP B

Method

μ₁: mean of GROUP A

µ₂: mean of GROUP B

Difference: μ₁ - µ₂

Equal variances are not assumed for this analysis.

Descriptive Statistics

Sample	N	Mean	StDev	SE Mean
GROUP A	12	10.33	5.28	1.5
GROUP B	12	12.00	6.22	1.8

Estimation for Difference

Difference	99% Upper Bound for Difference
-1.67	4.26

Test

Null hypothesis	H₀: μ₁ - µ₂ = 0
Alternative hypothesis	H₁: μ₁ - µ₂ < 0

T-Value	DF	P-Value
-0.71	21	0.244