orchidcrow943

orchidcrow943

Lv1

Mapua Institute of Technology

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Algebra1Statistics39
Given: (-x2+9)+(-3x2-11x+4) Solution: =(-x2+9)+(-3x2-11x+4) =-x2+9-3x2-11x+4 =...
A and B are independent. To prove, = So, and are independent The solution to t...
Frequency Distribution Table Scores Frequency, f Frequency Relative Value Cumu...
Answer: Dancer
Solution: Using your Calculator, input this. Press Shift then Divide Symbol fo...
When it comes to social contracts, in exchange for the safety of citizens and ...
Given: Ī¼=73 Ļƒ=9 Solution: a.) 45 and 70 P=(45<x<70) =0.3745-(1-0.9981) U...
Money is rain. Money falls from the sky like a gift from the gods, granted or ...
Please see attached file.

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.Ā  (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):

  1. A researcher hypothesizes that the effect of alcohol consumption on oneā€™s motor skills depends on the personā€™s weight (underweight, normal, overweight), but that this may differ for men versus women. (2 marks)

  2. A teacher is interested in seeing how attending class and reading the assigned chapters is related to her studentsā€™ 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)

1

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:

  1. What is the dependent variable? (0.5 marks)

  2. What are the independent variables (factors)? (0.5 marks)

  3. What is the research question(s) being addressed? (1 mark)

  4. What does the descriptive statistics (graphical) tell us about the effects under study?

    (1 mark)

  5. What assumptions are being tested in the R output? Are these assumptions met? Please

    provide statistical evidence. (2 marks)

  6. What effects are being tested in the R output? (1 mark)

  7. What does output from the ANOVA table tell us? (1 mark)

  8. What type of follow-up analyses was conducted and why? Please interpret. (2 marks)

2

: 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

3

> 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 ā€˜***ā€™ 0.001 ā€˜**ā€™ 0.01 ā€˜*ā€™ 0.05 ā€˜.ā€™ 0.1 ā€˜ ā€™ 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

57

> #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

54

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 ā€˜***ā€™ 0.001 ā€˜**ā€™ 0.01 ā€˜*ā€™ 0.05 ā€˜.ā€™ 0.1 ā€˜ ā€™ 1

4

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

5

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Between 81% and 87.4% of all adult residents have cellphones in a large city i...
Given: Ī¼=73 Ļƒ=9 Solution: a.) 45 and 70 P=(45<x<70) =0.3745-(1-0.9981) U...
Answer is attached.
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Solution: a.) Sample Mean = = 71,973.03 b.) 99,360 27,386.97 750,046,204.03 79...
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Solution: Interval Frequency,f Midpoint, x fx 25-34 20.9 29.5 616.55 18188.225...
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The answer is attached.
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The solution to your question is attached.
Answer is attached
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