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emeraldcamel410Lv1

25 Nov 2021

As part of a larger project to study the behavior of stressed-skin panels, a structural component being used extensively in North America, an article reported on various mechanical properties of Scotch pine lumber specimens. Data on the modulus of elasticity (MPa) obtained 1 minute after loading in a certain configuration and 4 weeks after loading for the same lumber specimens is presented here.

Observation 1 min 4 weeks Difference 1 10,450 9,130 1320 2 16,620 13,250 3370 3 17,500 14,720 2780 4 15,480 12,710 2770 5 12,960 10,120 2840 6 17,260 14,570 2690 7 13,400 11,220 2180 8 13,900 11,100 2800 9 13,630 11,420 2210 10 13,210 10,940 2270 11 14,370 12,110 2260 12 11,700 8,640 3060 13 15,470 12,590 2880 14 17,840 15,090 2750 15 14,060 10,550 3510 16 14,760 12,230 2530

Calculate an upper confidence bound for the true average difference between 1-minute modulus and 4-week modulus; first check the plausibility of any necessary assumptions. (Use 𝛼 = 0.05. Round your answer to two decimal places.)
MPa

Interpret your upper confidence bound.

We are 95% confident that the true mean difference between 1-minute modulus and 4-week modulus is never the upper bound. We are 95% confident that the true mean difference between 1-minute modulus and 4-week modulus is at least the upper bound. We are 95% confident that the true mean difference between 1-minute modulus and 4-week modulus is at most the upper bound. We are 95% confident that the true mean difference between 1-minute modulus and 4-week modulus is exactly the upper bound.

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Multiple Choice

1. You have a large dataset that will print on several pages. You want to ensure that related records print on the same page with column and row labels visible and that confidential information is not printed. You should apply all of the following page setup options except which one to accomplish this task?

(a) Set a print area.

(b) Print titles.

(d) Change the print page order.

2. You are working with a large worksheet. Your row headings are in column A. Which command(s) should be used to see the row headings and the distant information in columns X, Y, and 2?

(a) Freeze Panes command

(b) Hide Rows command

(d) Split Rows command

3. Which statement is not a recommended guideline for designing and creating an Excel table?

(a) Avoid naming two fields with the same name.

(b) Ensure that no blank columns separate data columns within the table.

(c)-Leave one blank row between records in the table.

(d) Include field names on the first row of the table.

4. Which of the following characters are wildcards in Excel? (Check all that apply.)

(a) *

(b) #

(e) ?

(d) $

5. What should you do to ensure that records in a table are unique?

(a) Do nothing; a logical reason probably exist to keep identical records.

(b) Use the remove duplicates command.

(d) Find the duplicate records and change some of the data to be different

6. Which Conditional Formatting rule is best suited to apply formatting to the top five values in a range of values?

(a) Above Average

(b) Greater Than

(c). Top 10 Items

(d) Between

7. Which date filter option enables you to restrict the view to only dates that occur in March of 2018?

(a) Equals

(b) Before

(d) Between

8. Which of the following is an unqualified structured reference?

(a) =[Purchase_Price]-[Down Payment]

(b) =Sales[Purchase_Price]-Sales[Down_Payment]

(d) =[Sales]Purchase_Price [Sales]Down_Payment

9. Which of the following is not an aggregate function that can be applied in a total row?

(a) MAX

(b) AVERAGE

(d) VLOOKUP

10. If you would like to set a conditional formatting rule based on the function=AND(G6"Finance". H7<7000), which formatting rule type is needed?

(a) Format all cells based on their values

(b) Format only cells that contain

(d) Format only values that are above or below average

burgundycoyote150

QUESTION 1What is the purpose of post hoc tests? Under what circumstances are post hoc tests not needed or appropriate?

a. Under what circumstances is ANOVA a more appropriate statistical technique to use than a t test for independent samples? Please provide an example(s) to support your answer. (2 marks)

b. (2 marks)

c. In testing the difference between group means, how are between group and within group variability related to each other? Provide an example to support your answer. (2 marks)

QUESTION 2

a. If a two-factor ANOVA results in a significant main effect for factor A and a significant AxB interaction, explain why you should be cautious in interpreting the effect of factor A. (1 mark)

b. For the following research situations what would be your main effects and interaction effect. If there was a significant interaction effect what would that mean? (please be as clear as possible in your explanation):

A researcher hypothesizes that the effect of alcohol consumption on one’s motor skills depends on the person’s weight (underweight, normal, overweight), but that this may differ for men versus women. (2 marks)
A teacher is interested in seeing how attending class and reading the assigned chapters is related to her students’ performance on tests. She assesses each student in terms of how often they attend class (rarely, sometimes, regularly) and how often they read the assigned chapters (rarely, sometimes, regularly). (2 marks)

QUESTION 3

Ethel is interested in two methods of note-taking strategies and the effect of these strategies on the overall GPAs of college freshmen. She believes that men would benefit most from Method 1, while women would benefit most from Method 2. After obtaining 30 men and 30 women volunteers in freshmen orientation, she randomly assigns 10 men and 10 women to Method 1, 10 men and 10 women to Method 2, and 10 men and 10 women to a control condition. During the first month of the spring semester individuals in the two note-taking method groups receive daily instruction on the particular note-taking method to which they were assigned. The control group receives no note-taking instruction. Fall and spring GPAs for all participants are recorded and a score that is the difference between the spring and fall semester GPAs is calculated.

Below are the results from running a two-way ANOVA. Please answer the following:

What is the dependent variable? (0.5 marks)
What are the independent variables (factors)? (0.5 marks)
What is the research question(s) being addressed? (1 mark)
What does the descriptive statistics (graphical) tell us about the effects under study?

(1 mark)
What assumptions are being tested in the R output? Are these assumptions met? Please

provide statistical evidence. (2 marks)
What effects are being tested in the R output? (1 mark)
What does output from the ANOVA table tell us? (1 mark)
What type of follow-up analyses was conducted and why? Please interpret. (2 marks)

: Men
: Method1

      median
coef.var

0.300

0.469

: Women
: Method1

      median
coef.var

0.150

0.496

: Men
: Method2

      median
coef.var

0.275

0.027

: Women
: Method2

      median
coef.var

0.600

0.629

: Men
: Control

      median
coef.var

0.175

mean 0.335

mean 0.170

mean 0.305

mean 0.640

mean 0.165

mean 0.105

skew.2SE
   0.408

SE.mean CI.mean.0.95

var 0.052

var 0.033

var 0.037

var 0.032

var 0.022

var 0.021

normtest.W
     0.936

std.dev
  0.229

0.682
    skewness

1.076
    skewness

0.630
    skewness

0.072

SE.mean CI.mean.0.95

normtest.p 0.830 -----------------------------------------------------------------------------

skew.2SE
   0.342

kurtosis
  -0.645

kurt.2SE
  -0.242

normtest.W
     0.964

0.058

SE.mean CI.mean.0.95

std.dev
  0.183

normtest.p 0.096 -----------------------------------------------------------------------------

skew.2SE
   0.361

kurtosis
  -1.363

kurt.2SE
  -0.511

normtest.W
     0.869

0.061

SE.mean CI.mean.0.95

std.dev
  0.192

normtest.p 0.857 -----------------------------------------------------------------------------

0.278
    skewness

0.904
    skewness

skew.2SE
  -0.124

kurtosis
  -1.096

kurt.2SE
  -0.411

normtest.W
     0.979

-0.171

: Women
: Control

      median
coef.var

0.100

1.392
    skewness

0.560

0.046

kurtosis
  -0.759

0.105

kurt.2SE
  -0.284

   std.dev
     0.146

normtest.p
     0.512

skew.2SE
   0.019

kurtosis
  -1.443

kurt.2SE
  -0.541

normtest.W
     0.967

skew.2SE
   0.458

kurtosis
  -0.770

kurt.2SE
  -0.289

normtest.W
     0.906

0.056

SE.mean CI.mean.0.95

std.dev
  0.178

normtest.p 0.254 -----------------------------------------------------------------------------

                                                                      std.dev
                                                                        0.149

normtest.p 0.958 -----------------------------------------------------------------------------

0.047

SE.mean CI.mean.0.95

0.164

0.131

0.137

0.127

0.107

> leveneTest(gpa$gpaimpr~gpa$gender, data=gpa,center=mean)

Levene's Test for Homogeneity of Variance (center = mean) Df F value Pr(>F)

group 1 7.09 0.01* 58

---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > leveneTest(gpa$gpaimpr~method, data=gpa,center=mean) Levene's Test for Homogeneity of Variance (center = mean)

      Df F value Pr(>F)
group  2    1.94   0.15

> #running Levene's test for assumption of HOV (INTERACTION EFFECT)
> leveneTest(gpa$gpaimpr, interaction(gpa$gender,gpa$method),center=mean) Levene's Test for Homogeneity of Variance (center = mean)

      Df F value Pr(>F)
group  5    0.57   0.72

Df Sum Sq Mean Sq F value Pr(>F) gender 1 0.020 0.020 0.61 0.43753

method 2 1.174 0.587 17.81 1.1e-06 *** gender:method 2 0.695 0.348 10.54 0.00014 *** Residuals 54 1.780 0.033
---

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

gender        0.0055
method        0.3200
gender:method 0.1894

0.011
0.397
0.281

eta.sq eta.sq.part

#selecting only Method1, run ANOVA, then follow-up tests

  Tukey multiple comparisons of means
    95% family-wise confidence level

Fit: aov(formula = gpaimpr ~ gender, data = gpaMethod1)
$`gender`
Women-Men -0.165 -0.3594851  0.02948506    0.0915581

diff        lwr        upr     p adj

#selecting only Method2, run ANOVA, then follow-up tests

  Tukey multiple comparisons of means
    95% family-wise confidence level

Fit: aov(formula = gpaimpr ~ gender, data = gpaMethod2)
$`gender`
Women-Men 0.335 0.161153 0.508847   0.000754

diff      lwr      upr    p adj

aquamarineox434

EX16_XL_CH05_GRADER_CAP_AS - Travel Expenses 1.3

Project Description:

You are the manager of an information technology (IT) team. Your employees go to training workshops and national conferences to keep up-to-date in the field. You created a list of expenses by category for each employee for the last six months. Now you want to subtotal the data to review total costs by employee and then create a PivotTable to look at the data from different perspectives.

Instructions:

For the purpose of grading the project you are required to perform the following tasks:

Step	Instructions	Points Possible
1	Start Excel. Open the downloaded Excel file named exploring_e05_grader_a1_Expenses.xlsx. Save the workbook as exploring_e05_grader_a1_Expenses_LastFirst, replacing LastFirst with your own name.	0.000
2	On the Subtotals worksheet, sort the data by Employee and further sort by Category, both in alphabetical order.	4.000
3	Use the Subtotals feature to insert subtotal rows by Employee to calculate the total expense by employee.	5.000
4	Collapse the Donaldson and Hart sections to show only their totals. Leave the other employees’ individual rows displayed.	5.000
5	Use the Expenses worksheet to create a blank PivotTable on a new worksheet named Summary. Name the PivotTable Categories.	8.000
6	Use the Category and Expense fields, enabling Excel to determine where the fields go in the PivotTable.	5.000
7	Modify the Values field to determine the average expense by category. Change the custom name to Average Expense.	4.000
8	Format the Values field with Accounting number type.	3.000
9	Type Category in cell A3 and change the Grand Totals layout option to On for Rows Only.	5.000
10	Apply Pivot Style Dark 2 and display banded rows. Note, depending upon the version of Office being used, the style name may be Light Blue, Pivot Style Dark 2.	5.000
11	Insert a slicer for the Employee field, change the slicer height to 2 inches and apply the Slicer Style Dark 5. Move the slicer below the PivotTable. Note, depending upon the version of Office being used, the style name may be Light Blue, Slicer Style Dark 5.	5.000
12	Use the Expenses worksheet to create another blank PivotTable on a sheet named Totals. Add the Employee to the Rows and add the Expense field to the Values area. Sort the PivotTable from largest to smallest expense.	10.000
13	Change the name for the Expenses column to Totals and format the field with Accounting number format.	4.000
14	Insert a calculated field to subtract 2659.72 from the Expense field. Format the field with the custom name Above or Below Average and apply Accounting number format to the field.	10.000
15	Set 12.25 width for column B and column C, change the row height of row 3 to 30, and apply word wrap to cell C3.	4.000
16	Create a clustered column PivotChart from the PivotTable. Move the PivotChart to a new sheet named Chart. Hide all field buttons in the PivotChart, if necessary. Note, Mac users, select the range A3:C8 in the PivotTable. On the Insert tab, click Recommended Charts, and then click Clustered Column to make the chart.	10.000
17	Add a chart title above the chart and type Expenses by Employee. Change the chart style to Style 14.	6.000
18	Apply 11 pt font size to the value axis and display vertical axis as Accounting with zero decimal places.	4.000
19	Create a footer on all worksheets with your name in the left section, the sheet name code in the center section, and the file name code in the right section.	3.000
20	Ensure that the worksheets are correctly named and placed in the following order in the workbook: Subtotals, Summary, Chart, Totals, Expenses. Save the workbook. Close the workbook and then exit Excel. Submit the workbook as directed.	0.000
	Total Points	100.000

https://www.dropbox.com/s/m7falnl85tfazl9/Torres%20DaSilva_exploring_e05_grader_a1_Expenses.xlsx?dl=0

bronzeelk977

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