probability SPSS

could somebody help me finish this spss homework

BC and Fat

Intake, Selected Countries

Vegetable Fat

Intake (gm/day) Intake (gm/day)

38.7850

18.6916

22.4299

28.5714

20.0000

28.5047

7.9927

7.6636

21.3187

	Breast Cancer Death Rates, Animal and	Vegetable Fat
[Source: K. K. Carroll, “Experimental Evidence of Dietary Factors and Hormone-Dependent Cancers,”
Cancer Research 35(1975):3374-3383]
Country	Animal Fat	Total Fat	Age Adjusted Mortality Rate
		Intake (gm/day)	(per 100,000 population)
Australia	14.5055	1 Save Time On Research and Writing Hire a Pro to Write You a 100% Plagiarism-Free Paper. Get My Paper	20.0000	134.5055	19.4891
Austria	40.9670	84.1121	125.0792	17.2993
Belgium	47.1209	98.1308	145.2517	21.4599
Bulgaria	38.6813	32.2430	70.9243	9.1971
Canada	23.2967	1	22.4299	145.7266	23.8686
Chile	24.1758	35.5140	59.6898	8.9781
Columbia		21.3187		28.5047	49.8234	5.4745
Czechoslovakia		28.5714	70.0935	98.6649	15.0000
Denmark	27.4725	135.0467	162.5193	24.0876
El Salvador	27.9121	15.2336	43.1457	0.8759
Finland	14.0659	105.1402	119.2061	13.6861
France	42.9890	100.0000	142.9890	16.4234
Germany	45.2747	94.8598	140.1345	17.7372
Greece	61.5385	37.3832	98.9216		7.9927
Hong Kong	36.4835		38.7850	75.2686	10.0073
Hungary	17.1429	87.3832	104.5260	13.7299
Ireland	22.4176	1	18.6916	141.1092	21.8978
Italy	52.5275	91.3125	15.8759
Japan	29.8901	48.5817	3.7226
Mexico	39.1209	61.5508	4.2701
Netherlands	56.4835	103.7383	160.2218	26.0146
New Zealand	13.1868	14	7.6636	160.8504	23.5401
Norway	108.8785	137.4499	17.0803
Panama	40.7473	20.0935	60.8407	7.5328
Philippines	18.0220	16.3551	34.3771	4.8175
Poland	75.7009	95.7009	10.4015
Portugal	46.5934	75.0981	12.9197
Puerto Rico	15.2527	65.8879	81.1406	6.4161
Romania	31.6484	41.5888	73.2371
Spain	63.5165	38.3178	101.8342	8.6496
Sri Lanka	42.6374	50.3009	2.1898
Sweden	38.2418	98.5981	136.8399	18.8321
Switzerland	55.1648	88.3178	143.4826	22.3358
Taiwan	27.1028	48.4215	3.8978
Thailand	19.1209	11.2150	30.3358	0.6569
United Kingdom	26.3736	119.6262	145.9998	24.5255
United States	52.7473	102.3364	155.0837	21.1314
Venezuela	32.0000	33.6449	65.6449	8.5401
Yugoslavia	31.2088	43.1776	74.3864	7.4234

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oach Salary

ye Color

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																														E	Salary (in dollars)		Salary Range
																												1	22516												A
26425
29294
37116											B
41012
49806
51303
56477
61563
70295
71119
71662
73136
74574
84744											D
86053
86256
88901
92408
94666
98750
105363
112845
128443
159829
161341
286274				F
291587
22735
28525
28989
31865
32880
32934
34113
34764
38300
39428
40945
42545
43973
47278
49610
51980
56425
62148
82321
88219
88325
128084
128570
220092

Codes

Salary Range A

B

C

D

E

F

1

2

< $35,000
$35,000 – $50,000
$50,001 – $80,000
$80,001- $100,000
$100,001 – $200,000
> $200,000
Eye Color	Green
Not Green

Usethis document file or open a new MS-Word document to enter the answers to these questions.

1. Coaches’ Salaries

A. Basic Single Variable Descriptive Statistics

Open the CoachesSalaries.xlsx file in Excel. It is a set of coaches’ salaries gathered in Tennessee in 2010.

“Clean up” the file, as described in class, if necessary. If you modified the file, save it and close it.

Open the CoachesSalaries.xlsx file in SPSS.

Use SPSS to find the following descriptive statistics for the coaches’ Salary in Dollars. (include a frequency table)

Minimum

Maximum

Range

Median

Q values

Mean

Standard Deviation

Use SPSS to create a histogram of the coaches’ Salary in Dollars with a projected normal curve included.

Calculate the z-scores for all coaches’ Salary in Dollars. (You do not need to copy and paste the z-scores into your Word document.)

1. Copy the Salary in Dollars “statistics box” from the SPSS output and paste it into your Word document.

2. Copy the Salary in Dollars frequency table from the SPSS output and paste it into your Word document.

3. Copy the Salary in Dollars histogram from the SPSS output and paste it into your Word document.

4. Review the Salary in Dollars “statistics box”. Based on your review, list the values of the following:

a. Q1

b. Q2

c. Q3

d. Q4

e. Mean

f. Median

g. Standard Deviation

5. Review the Salary in Dollars histogram. Based on that review:

a. Do the salaries appear to be a normal distribution?

b. Defend your answer to 5.a.

c.
Based on your histogram review alone
, are there any Salary in Dollars outlier candidates?

d. If there are outlier candidates, list the Salary in Dollars value(s) of the outlier candidate(s).

6. Review the Salary in Dollars z-scores for this distribution. Based on that review:

a. Are there any Salary in Dollars outlier candidates?

b. If so, list the outlier candidate Salary in Dollars values and their corresponding z-scores

7. Are your answers to 1. A. 5. c. and d. (above) the same as your answers to 1.A.6. a and b (above) ?

(Do both identify the same outliers…or no outliers?)

B. Cross-tabulation – Two-variable statistics

1. Add decode values to the

a. Salary Range variable

b. Eye Color variable

Use SPSS to cross-tabulate the Salary Range and Eye Color variables

2. Copy the cross-tabulation matrix found in SPSS output and paste it into your Word document.

2. Breast Cancer Data

Open the BreastCancerData.xlsx file in Excel. It contains data on breast cancer and fat intake for several countries.

Clean the file up, as described in class, if necessary. If you modify the file, save and close it.

Open the BreastCancerData.xlsx file with SPSS.

(After you have loaded your variables into SPSS, I recommend that you reduce the “Decimal Places” attribute for each variable to 5.)

Use SPSS to analyze this data, including:

A. Basic Single Variable Descriptive Statistics

Use SPSS to find the following descriptive statistics for Age-Adjusted Breast Cancer Mortality.

Minimum
Maximum
Range
Median
Q values
Mean
Standard Deviation

Prepare a histogram with projected normal curve for Age-Adjusted Breast Cancer Mortality.

Calculate the z-scores of all values for Age-Adjusted Breast Cancer Mortality. You do not need to copy and paste the z-scores onto your Word document.

1. Copy the Age-Adjusted Breast Cancer Mortality “statistics box” from the SPSS output and paste them into your Word document.

2. Copy the Age-Adjusted Breast Cancer Mortality frequency table from the SPSS output and paste them into your Word document.

3. Copy the Age-Adjusted Breast Cancer Mortality histogram from the SPSS output and paste it into your Word document.

Review the Age-Adjusted Breast Cancer Mortality statistics box.

Review the Age-Adjusted Breast Cancer Mortality frequency table.

Based on your review:

4. List the values of the following:

a. Q1
b. Q2

c. Q3

d. Q4
e. Mean
f. Median
g. Standard Deviation

5. For Age-Adjusted Breast Cancer Mortality, what percent of countries are higher than Japan?

6. For Age-Adjusted Breast Cancer Mortality, what percent of the countries are at or below France?

7. For Age-Adjusted Breast Cancer Mortality, in which quartile is Poland?

Review the Age-Adjusted Breast Cancer Mortality histogram

8. Based
only
on your review of the Age-Adjusted Breast Cancer Mortality histogram:

a. Based on your Age-Adjusted Breast Cancer Mortality histogram analysis alone, are there any Age- Adjusted Breast Cancer Mortality outlier candidates?

b. If there are outlier candidates, list the Age-Adjusted Breast Cancer Mortality value(s) on your Word document

Review the z-scores of the Age-Adjusted Breast Cancer Mortality distribution.

9. Based on your review of the z-scores for Age-Adjusted Breast Cancer Mortality:

a. What is the z-score for The Netherlands ?

b. Based on the z-score, is The Netherlands an outlier candidate?

c. Based on the Age-Adjusted Breast Cancer Mortality z-scores, are there any outlier candidates ?

d. If there are outlier candidates based on z-score analysis, which Age-Adjusted Breast Cancer Mortality values are they and what are their z-scores ?

B. Correlation – Two variable statistics

Use SPSS to calculate the Pearson R values for each of the following pairs of variables:

Breast cancer mortality and animal fat intake

Breast cancer mortality and vegetable fat intake

Breast cancer mortality and total fat intake

Use SPSS to prepare scatter plots (with trend line) for each of the following pairs of variables:

Breast cancer mortality and animal fat intake
Breast cancer mortality and vegetable fat intake
Breast cancer mortality and total fat intake

1. For Breast cancer mortality and animal fat intake

a. Copy the “R box” from the SPSS output and paste it into your Word document.

b. Copy the scatter plot for from the SPSS output and paste it into your Word document.

c. What is the value of the Pearson R?

d. Based on the value of the Pearson R, is there a correlation between breast cancer mortality and animal fat intake ?

e. If there is a correlation between Breast cancer mortality and animal fat intake, is it positive or negative ?

f. If there is a correlation between Breast cancer mortality and animal fat intake, is it strong or moderate or weak ?

g. 1. Based on your analysis of the correlation between Breast cancer mortality and animal fat intake, can you conclude that animal fat intake causes breast cancer ?

2.Why, or why not ?

2. For Breast cancer mortality and vegetable fat intake

a. Copy the “R box” from the SPSS output and paste it into your Word document.
b. Copy the scatter plot for from the SPSS output and paste it into your Word document.
c. What is the value of the Pearson R?

d. Based on the value of the Pearson R, is there a correlation between breast cancer mortality and vegetable fat intake ?

e. If there is a correlation between Breast cancer mortality and vegetable fat intake, is it positive or negative ?

f. If there is a correlation between Breast cancer mortality and vegetable fat intake, is it strong or moderate or weak ?

g. 1. Based on your analysis of the correlation between Breast cancer mortality and vegetable fat intake, can you conclude that vegetable fat intake causes breast cancer ?

2.Why, or why not ?

3. For Breast cancer mortality and total fat intake

a. Copy the “R box” from the SPSS output and paste it into your Word document.
b. Copy the scatter plot for from the SPSS output and paste it into your Word document.
c. What is the value of the Pearson R?

d. Based on the value of the Pearson R, is there a correlation between breast cancer mortality and total fat intake ?

e. If there is a correlation between Breast cancer mortality and total fat intake, is it positive or negative ?

f. If there is a correlation between Breast cancer mortality and total fat intake, is it strong or weak or moderate ?

g. 1. Based on your analysis of the correlation between Breast cancer mortality and total fat intake, can you conclude that total fat intake causes breast cancer ?

2.Why, or why not ?

3. Statistics In Everyday Use

Find three articles in the popular media (e.g. newspaper, web-site) that include statistics (presented as numbers or as graphics or in both ways.)

These should be three separate articles/sources, not three examples of statistics in one article

A. For each article/statistic:

1. Summarize the article and the statistic(s) it contains briefly, or copy the article, including the statistic(s) you are critiquing, into your Word document.

2. Include a citation of the source of the article.

B. For each article/statistic:

1. Do you think that the statistic or the way it is used/presented is deceptive?

2. Why or why not?

3. What is your evidence?

7 of 7

1 of 2

LSP 121 – Individual Assignment #1 – General Feedback

Use SPSS to calculate all statistics and prepare graphs.

Make sure that items copied from SPSS output and pasted to the submission document do not lose the “box” outline and
format. I will expect similar items to be copied and pasted successfully (with box and outline) on the exam.

1. A. Basic Descriptive Statistics
Include both the stats box and the frequency table
Include only the Salary variable, not the eye color and not the salary range
z-scores for outliers are greater than +2 or less than -2…..give the variable value itself

B. Frequency Distribution Presentation – histogram
This is not a normal distribution
There are outliers – give the values of the outliers, check the frequency table for specific values
Consistency – are the outliers values you found by zscore and by histogram examination the same ?

C. Another Frequency Distribution Presentation – Cross-tabulation
Include the Crosstab…not the Case Processing Summary
Crosstab should be between the two categorical variables – Eye Color and Salary Range
Include decode values for the variables
Put the variable with more values in the row

2. A. Basic Statistics and Correlation
Make sure the data in excel is cleaned up before importing it to SPSS – if there are missing values, you need to check the data in excel, clean it up
and import again

Include the stats box, frequency table, and histogram
Find the percentile on the frequency table – cumulative percentage column
Compare the value with Q1, Q2 and Q3 to find the quartile

2 of 2

B. Correlation
Prepare one R box and scatter plot for each pair of variables…each fat vs mortality rate
Include a trend line on the scatter plot
Use R, not R-squared
All are positive. Two are strong, one is weak
Correlation does not mean causation

3. Statistics in Everyday Use
Provide three examples
Are each of the examples deceptive ? (not descriptive)