Spss final | Numerical analysis homework help

 

152 pts total

 

For Questions 1-2 use the 7 step process to answer. Refer to slides if you are unsure of the 7 step process.  PLEASE DON’T OMIT ANY PART OF THE PROCESS!!! (40 pts) THIS IS DONE IN SPSS USING BREAST CANCER AND OBESITY DATASET

 

Dataset Background – PLEASE READ:

Obesity is very common in American society and is a risk factor for breast cancer for postmenopausal women.  One mechanism explaining why obesity is a risk factor is that it may raise estrogen levels in women.  In particular, one type of estrogen, serum estradiol, is a strong risk factor for breast cancer.  To better assess this relationship, researchers studied a group of 200 postmenopausal women.  The SPSS file is entitled, Breast Cancer and Obesity.

 

Adiposity was measured in two different ways:  (a) by body mass index (BMI) = weight (kg) / height(m2) and also (b) by waist-hip ratio (WHR) = waist circumference/hip circumference.  BMI is a measure of overall adiposity, whereas WHR is a measure of abdominal adiposity.  In addition, a complete hormonal profile was obtained, including serum estradiol.  Finally, other breast-cancer risk factors were also assessed among these women, including ethnicity, parity, age at first birth, and age at menarche.

 

Variable           Column           Code    Label                                       Values (if categorical)

Id                           1                Identification number

ES_1                      2                Serum Estradiol

ETHNIC               3                Ethnicity                                 1 = African-American, 0 = Caucasian

NUMCHILD        4                Parity, number of children

AGEFBO              5                Age at 1st birth                                    (missing a response if never had a child)

ANYKIDS            6                Gave birth to any children?    1 = Yes, 0 = No

AGEMENAR      7                Age at menarche

BMI                      8                Body Mass Index

WHR                       9              Waist-hip ratio

**Missing responses are left blank

 

ALSO THE FOLLOWING CONTINUOUS VARIABLES HAVE BEEN CATEGORIZED!!

    • BMI has been categorized, bmi_cat, :  normal BMI (<25) and abnormal BMI (25 or greater).
    • Menarche has been categorized, menarche_cat, two categories – 9-12 and 13-16
  • WHR has also been categorized, whr_category, 3 categories – 0-.69, .7-.79, and .8 and greater

 

1.      Is there a statistically significant difference in mean estradiol between African Americans and Caucasions?

 

a.     Provide a visual aid depicting the mean differences between the two groups.

 

2.      Is there a statistically significant difference in mean estradiol between ethnicity status depending on BMI_CAT (using the categorized variable, so normal or abnormal groups)?

 

 

 

3.     Please use the rock climbing performance dataset.  Here is the description:  This is research done by a senior at PSU-Berks.  He was interested in determining the effects of imagery on rock climbing performance.  He chose 20 experienced rock climbers.  With randomization on the order, he had them climb with no imagery on a rock wall and then had them climb with imagery (on a different but same difficulty wall).  Ignoring issues of confounding, can we conclude that imagery decreases rock wall climb time (in seconds)? (15pts)

a.     What statistical test should be used?

b.     Please report the results and provide an overall and formal conclusion. Be sure to include ALL necessary information.

 

 

 

 

Questions 4 – 7:  Please view the below output of the linear regression test and answer the following questions (20 pts total)

 

                                                          Coefficients(a)

 

  

 

  

 

 

Model

 

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

30.190

7.221

 

4.181

.000

Body mass index

.537

.278

.136

1.933

.055

a  Dependent Variable: Estradiol

 

 

 

4.     What is the dependent variable and what is the independent variable?

 

 

5.     Please write out the regression prediction equation

 

 

6.     Please interpret the slope and the intercept in terms of the original variables.

 

 

a.     Are they significant?  Why or why not?

 

 

b.     Please report APA results.

 

 

 

7.     The p-value is a probability.  Specifically it is the probability of what?

 

Conceptual Problems (3 pts each – 23 pts total)

 

8.      You are a professor and want to report to the class the quiz score that will most accurately depict the value of centrality of everyone’s quiz scores.  Below is a table of the 18 students’ results.  Enter into SPSS and answer the below questions. 

90

90

91

91

100

36

90

89

22

95

97

95

40

90

38

90

92

91

a.      Is the continuously measured quiz score normally distributed or positively/negatively skewed? Provide evidence for your answer using both a histogram and the skewness/std error value.

 

 

b.     Based off your answer in Part A above, is the mean or median then a more accurate reflection of the class’ quiz score centrality?  Why?   Be sure to include in your answer the mean and median quiz score values.

 

9.      If I have a a heart rate variable measured as High, Moderate, and Low (bpm) and I want to see if there is a significant difference between the three categories for some dependent variable would I need to run a post hoc analysis?? Why or why not??

 

10.  A study is conducted to assess the effects experience in sports has on coping with stress.  Three categories are used for experience, more than ten years, 5-10 years and less than 5 years.  We want to see if there is a difference in sress coping (measured continuously) between the three groups.  Results are F(2,50) = 5.43, p=.043.  It is concluded that because of p<.05 the ten year group is significantly greater than the 5-10 year group and the less than 5 year group.  Is this a correct statement?? If not, please state why not.

 

 

11.  In a correlation study an r=.8 is found.  It is therefore concluded that variable x causes an increase in variable y.  Is this true or false??  Please state why not if it isn’t.

 

 

12.  In a Levene’s test for homogeneity of variance, a p value of .78 is found.  It is concluded because the p value is greater than .05 we reject the null and conclude varaiances can be assumed equal.  True or false??  Please correct if false.

 

 

13.  What is meant when I say a particular statistical test is an omnibus test?

 

 

 

Guess the Test – report IV, DV and all levels and type of measurement and the appropriate statistical test (15 pts total)

 

14.   A researcher is interested in the effects muscle soreness has on power.  15 participants come are tested before an intense cardio/plyometric training bout on their vertical jump.  After the initial test, they are put through an intense training session to invoke muscle soreness.  The participants come back in the following day, and each day after until day 4 to be re-teseted on their vertical jump.  We want to know if there is a decrease in vertical jump scores across the measurement periods.

 

15.  A researcher wants to see if the the rectus abdominus muscle has higher EMG amplitude while using an Ab Rocket compared to a standared sitting crunch.  The participant is tested on the Ab Rocket and then tested doing a crunch.  We want to see if the muscle activity is higher in the ab rocket compared to the standard crunch

 

 

16.  A researcher would like to see if there is a significant difference in exercise enjoyment (measured continuously) between exercise status groups (high intensity, moderate intensity, control).

 

 

Use the below output to answer the questions.  A one way ANOVA was run to see if there were significant differences in mean estradiol between WHR (waist hip ratio) categories. (15 pts total)

 

                                                                                   Descriptives

 

 

 

 

 

 

Estradiol

     

 

  

 

N

Mean

Std. Deviation

Std. Error

95% Confidence Interval for Mean

Minimum

Maximum

Lower Bound

Upper Bound

0-.69

27

45.7348

16.89906

3.25223

39.0498

52.4199

20.67

78.00

.70-.79

125

40.7233

19.79922

1.77090

37.2182

44.2284

12.00

120.00

.8 and greater

48

50.9721

23.32412

3.36655

44.1995

57.7447

17.00

146.00

Total

200

43.8596

20.71044

1.46445

40.9717

46.7474

12.00

146.00

 

         Test of Homogeneity of Variances

 

Estradiol

Levene Statistic

df1

df2

Sig.

.488

2

197

.615

 

                                                         ANOVA

 

Estradiol

 

Sum of Squares

df

Mean Square

F

Sig.

Between Groups

3752.703

2

1876.351

4.530

.012

Within Groups

81602.857

197

414.228

 

 

Total

85355.560

199

 

 

 

 

                                                            Multiple Comparisons

 

Dependent Variable: Estradiol

Bonferroni

     

 

 

 

 

 

 

 

(I) whr_category

(J) whr_category

Mean Difference (I-J)

Std. Error

Sig.

95% Confidence Interval

Lower Bound

Upper Bound

0-.69

.70-.79

5.01153

4.31921

.742

-5.4176

15.4407

.8 and greater

-5.23727

4.89607

.858

-17.0593

6.5848

.70-.79

0-.69

-5.01153

4.31921

.742

-15.4407

5.4176

.8 and greater

-10.24880(*)

3.45595

.010

-18.5935

-1.9041

.8 and greater

0-.69

5.23727

4.89607

.858

-6.5848

17.0593

.70-.79

10.24880(*)

3.45595

.010

1.9041

18.5935

*  The mean difference is significant at the .05 level.

 

 

 

17.  Please write out the null and research hypothesis

 

18.   What does the homogeneity of variance test tell us?  What is the result?

 

 

19.  Please write the results of the ANOVA in APA format.  Do we reject the null or fail to reject the null?

 

20.  Are post hocs necessary?? If so, please report which conditions are significant from one another.

 

 

21.  What are the other assumptions that go into the one way ANOVA?

 

 

For the next set of questions, please read the datset description and then run the appropriate analysis.  No output is required.  Please just run the analysis and report JUST the results and your conclusion to the question…BE SURE TO INCLUDE ALL IMPORTANT/RELEVANT INFORMATION TO A CONLUSION!

(20pts)

22.  Dataset:  football punters

Description – Investigators studied physical characteristics and ability in 13 football punters. Each volunteer punted a football ten times. The investigators recorded the average distance for the ten punts, in feet. They also recorded the average hang time (time the ball is in the air before the receiver catches it) for the ten punts, in seconds. In addition, the investigators recorded five measures of strength and flexibility for each punter: right leg strength (pounds), left leg strength (pounds), right hamstring muscle flexibility (degrees), left hamstring muscle flexibility (degrees), and overall leg strength (foot-pounds). Taken from the study “The relationship between selected physical performance variables and football punting ability” by the Department of Health, Physical Education and Recreation at the Virginia Polytechnic Institute and State University, 1983.

a.     Question:  Is left leg strength significantly different from right leg strength?

b.     Question:  Can overall leg strength predict the average punt distance?

 

 

 

 

 

 

 

 

 







Calculate Your Essay Price
(550 words)

Approximate price: $22

Calculate the price of your order

550 words
We'll send you the first draft for approval by September 11, 2018 at 10:52 AM
Total price:
$26
The price is based on these factors:
Academic level
Number of pages
Urgency
Basic features
  • Free title page and bibliography
  • Unlimited revisions
  • Plagiarism-free guarantee
  • Money-back guarantee
  • 24/7 support
On-demand options
  • Writer’s samples
  • Part-by-part delivery
  • Overnight delivery
  • Copies of used sources
  • Expert Proofreading
Paper format
  • 275 words per page
  • 12 pt Arial/Times New Roman
  • Double line spacing
  • Any citation style (APA, MLA, Chicago/Turabian, Harvard)

Our guarantees

Delivering a high-quality product at a reasonable price is not enough anymore.
That’s why we have developed 5 beneficial guarantees that will make your experience with our service enjoyable, easy, and safe.

Money-back guarantee

You have to be 100% sure of the quality of your product to give a money-back guarantee. This describes us perfectly. Make sure that this guarantee is totally transparent.

Read more

Zero-plagiarism guarantee

Each paper is composed from scratch, according to your instructions. It is then checked by our plagiarism-detection software. There is no gap where plagiarism could squeeze in.

Read more

Free-revision policy

Thanks to our free revisions, there is no way for you to be unsatisfied. We will work on your paper until you are completely happy with the result.

Read more

Privacy policy

Your email is safe, as we store it according to international data protection rules. Your bank details are secure, as we use only reliable payment systems.

Read more

Fair-cooperation guarantee

By sending us your money, you buy the service we provide. Check out our terms and conditions if you prefer business talks to be laid out in official language.

Read more

Order your essay today and save 10% with the coupon code: best10