Correlation and Simple Regression Tables Template Hypothesis Testing: Correlation and Simple Reg

Correlation and Simple Regression Tables Template

Hypothesis Testing: Correlation and Simple
Regression
Assignment Overview

In this assignment, you are given data to determine the relationship between
pairs of variables.

Based on the descriptive data, you will choose the appropriate correlation
analysis and interpret the strength and direction of the correlation and its
statistical significance. Note: For some of the correlation pairs, it is appropriate to
examine the ability to predict one variable from the other.

To successfully complete this assignment, you must address the following:

● Describe the types of relationships that can occur between two variables.
● Determine which correlation analysis is appropriate, based on the type of

data collected.
● Describe the information that can be gleaned from a correlation analysis.
● Describe the role of linear regression analysis.
● Interpret a simple linear regression output.

Preparation for the Assignment

The following files must be downloaded from Resources to complete this
assignment:

● Correlation and Simple Regression Tables Template (includes Data
Description).

● Unit 8 SPSS Output [PDF].

Instructions for the Assignment

Step 1: Data Validation

As with all new data sets, your first step is to do the data validation.

● Review the Unit 8 SPSS Output [PDF] and note any issues with the data.

Step 2: Correlation

Establish the relationships of the variables using the following correlation
procedures. Based on your data validation, choose the appropriate correlation
coefficient and interpret the strength, direction, and significance of the correlation
for six variable pairs of your choice.

● Review both the Pearson correlations (parametric) and the Spearman
rank-order correlations.

Step 3: Simple Regression

● Interpret the appropriate simple regression results for your variables.

Additional Requirements

● Create a document that is clearly written and generally free of grammatical
errors.

u08a1 Correlation and Simple Regression Tables Template

Use this data description for both the correlation and the simple regression tables.

In the beginning of a health intervention program, the participants were given extensive measurements of body composition. These measurements were the following:

· Percentage of body fat (BODYFAT).

· Height (cm).

· Weight (kg).

· Circumference measures (cm) of the neck, chest, abdomen, hip, thigh, and biceps.

· BMI and Waist/Hip ratio were calculated, using the abdominal circumference as the waist.

· Age was also recorded.

For this study, no demographic information was recorded.

Correlation Table

Write out your six variables here. Change the name of variable x to the variable name. Enter the correlation coefficient in the cell. Use an asterisk (*) to label significant finds (p ( 0.05). Italicize Spearman correlation coefficients.

	Variable 4	Variable 5	Variable 6
Variable 1
Variable 2
Variable 3

After you are done with the correlation table, you will chose the Weight, Abdomen, BMI, Waist/Hip Ratio, and Age variables to regress on BODYFAT on the following pages.

Report Results and Interpretation of Regression Analysis

Use the results of the regression analysis to predict the percentage of body fat if a person weighs 60 kg, has an abdominal circumference of 88 cm, a BMI of 22.6, and Waist/Hip ratio 1.3.

Regression Analysis Table

Regression of weight, abdomen, BMI, W/H ratio, and age on percentage of body fat:

SEE

(

Weight

Abdomen

BMI

Waist/Hip ratio

Age

Interpretation of Regression

Predicted values of body fat percentage

Variable	Known amount	% Body fat’ (predicted)
Weight (kg)	60
Abdomen (cm)	88
BMI (kg/m2)	22.6
Waist/Hip ratio	1.3

Page 1

Explore

Notes

Output Created 20-SEP-2017 13:57:26

Comments

Input Data /Users/Rick/Desktop/PU
B4009/spss/FAT.sav

Active Dataset DataSet1

Filter < n o n e >

Weight < n o n e >

Split File < n o n e >

N of Rows in Working
Data File

2 5 2

Missing Value Handling Definition of Missing User-defined missing
values for dependent
variables are treated as
missing.

Cases Used Statistics are based on
cases with no missing
values for any
dependent variable or
factor used.

Page 2

Notes

Syntax EXAMINE
VARIABLES=BODYFAT
AGE HEIGHT WEIGHT
NECK CHEST ABDOMEN
HIP THIGH BICEPS BMI
WAISTHIPRATIO
/PLOT NONE
/PERCENTILES
(5,10,25,50,75,90,95)
HAVERAGE
/STATISTICS
DESCRIPTIVES EXTREME
/CINTERVAL 95
/MISSING LISTWISE
/NOTOTAL.

Resources Processor Time 00:00:00.03

Elapsed Time 00:00:00.00

Page 3

Case Processing Summary

Valid

Percent N

Cases

Missing

Percent N

Total

Percent

BODYFAT 2 5 2 100.0% 0 0.0% 2 5 2 100.0%

AGE 2 5 2 100.0% 0 0.0% 2 5 2 100.0%

HEIGHT 2 5 2 100.0% 0 0.0% 2 5 2 100.0%

WEIGHT 2 5 2 100.0% 0 0.0% 2 5 2 100.0%

NECK 2 5 2 100.0% 0 0.0% 2 5 2 100.0%

CHEST 2 5 2 100.0% 0 0.0% 2 5 2 100.0%

ABDOMEN 2 5 2 100.0% 0 0.0% 2 5 2 100.0%

HIP 2 5 2 100.0% 0 0.0% 2 5 2 100.0%

THIGH 2 5 2 100.0% 0 0.0% 2 5 2 100.0%

BICEPS 2 5 2 100.0% 0 0.0% 2 5 2 100.0%

BMI 2 5 2 100.0% 0 0.0% 2 5 2 100.0%

WAISTHIPRATIO 2 5 2 100.0% 0 0.0% 2 5 2 100.0%

178.9244 1.85134 Page 4

Descriptives

Statistic Std. Error

BODYFAT Mean 18.938 . 4 8 8 3

95% Confidence Interval
for Mean

Lower Bound 17.977

Upper Bound 19.900

5% Trimmed Mean 18.865

Median 19.000

Variance 60.076

Std. Deviation 7.7509

Minimum . 0

Maximum 4 5 . 1

Range 4 5 . 1

Interquartile Range 1 1 . 8

Skewness . 1 4 4 . 1 5 3

Kurtosis – . 3 0 7 . 3 0 6

AGE Mean 4 4 . 8 8 . 7 9 4

95% Confidence Interval
for Mean

Lower Bound 4 3 . 3 2

Upper Bound 4 6 . 4 5

5% Trimmed Mean 4 4 . 5 9

Median 4 3 . 0 0

Variance 158.811

Std. Deviation 12.602

Minimum 2 2

Maximum 8 1

Range 5 9

Interquartile Range 1 9

Skewness . 2 8 4 . 1 5 3

Kurtosis – . 4 1 6 . 3 0 6

Page 5

Descriptives

37.992 . 1 5 3 1

Statistic Std. Error

HEIGHT Mean 178.9244 1.85134

95% Confidence Interval
for Mean

Lower Bound 175.2783

Upper Bound 182.5706

5% Trimmed Mean 177.8604

Median 176.5000

Variance 863.723

Std. Deviation 29.38916

Minimum 118.50

Maximum 363.15

Range 244.65

Interquartile Range 3 8 . 5 0

Skewness 1 . 2 0 5 . 1 5 3

Kurtosis 5 . 2 7 0 . 3 0 6

WEIGHT Mean 70.1488 .23074

95% Confidence Interval
for Mean

Lower Bound 69.6944

Upper Bound 70.6032

5% Trimmed Mean 70.2837

Median 70.0000

Variance 13.417

Std. Deviation 3.66286

Minimum 2 9 . 5 0

Maximum 7 7 . 7 5

Range 4 8 . 2 5

Interquartile Range 4 . 0 0

Skewness – 5 . 3 8 5 . 1 5 3

Kurtosis 59.544 . 3 0 6

Page 6

Descriptives

92.556 . 6 7 9 3

Statistic Std. Error

NECK Mean 37.992 . 1 5 3 1

95% Confidence Interval
for Mean

Lower Bound 37.690

Upper Bound 38.294

5% Trimmed Mean 37.967

Median 38.000

Variance 5 . 9 0 9

Std. Deviation 2.4309

Minimum 3 1 . 1

Maximum 5 1 . 2

Range 2 0 . 1

Interquartile Range 3 . 1

Skewness . 5 5 3 . 1 5 3

Kurtosis 2 . 7 2 0 . 3 0 6

CHEST Mean 100.824 . 5 3 1 1

95% Confidence Interval
for Mean

Lower Bound 99.778

Upper Bound 101.870

5% Trimmed Mean 100.484

Median 99.650

Variance 71.073

Std. Deviation 8.4305

Minimum 7 9 . 3

Maximum 1 3 6 . 2

Range 5 6 . 9

Interquartile Range 1 1 . 3

Skewness . 6 8 2 . 1 5 3

Kurtosis . 9 8 7 . 3 0 6

Page 7

Descriptives

59.406 . 3 3 0 7

Statistic Std. Error

ABDOMEN Mean 92.556 . 6 7 9 3

95% Confidence Interval
for Mean

Lower Bound 91.218

Upper Bound 93.894

5% Trimmed Mean 92.130

Median 90.950

Variance 116.275

Std. Deviation 10.7831

Minimum 6 9 . 4

Maximum 1 4 8 . 1

Range 7 8 . 7

Interquartile Range 1 5 . 1

Skewness . 8 3 8 . 1 5 3

Kurtosis 2 . 2 4 9 . 3 0 6

HIP Mean 99.905 . 4 5 1 3

95% Confidence Interval
for Mean

Lower Bound 99.016

Upper Bound 100.794

5% Trimmed Mean 99.585

Median 99.300

Variance 51.324

Std. Deviation 7.1641

Minimum 8 5 . 0

Maximum 1 4 7 . 7

Range 6 2 . 7

Interquartile Range 8 . 1

Skewness 1 . 4 9 7 . 1 5 3

Kurtosis 7 . 4 7 1 . 3 0 6

Descriptives

23.456 . 4 3 5 9 Page 8

Statistic Std. Error

THIGH Mean 59.406 . 3 3 0 7

95% Confidence Interval
for Mean

Lower Bound 58.755

Upper Bound 60.057

5% Trimmed Mean 59.226

Median 59.000

Variance 27.562

Std. Deviation 5.2500

Minimum 4 7 . 2

Maximum 8 7 . 3

Range 4 0 . 1

Interquartile Range 6 . 5

Skewness . 8 2 1 . 1 5 3

Kurtosis 2 . 6 6 6 . 3 0 6

BICEPS Mean 32.273 . 1 9 0 3

95% Confidence Interval
for Mean

Lower Bound 31.899

Upper Bound 32.648

5% Trimmed Mean 32.257

Median 32.050

Variance 9 . 1 2 8

Std. Deviation 3.0213

Minimum 2 4 . 8

Maximum 4 5 . 0

Range 2 0 . 2

Interquartile Range 4 . 2

Skewness . 2 8 6 . 1 5 3

Kurtosis . 4 9 8 . 3 0 6

Page 9

Descriptives

Statistic Std. Error

BMI Mean 23.456 . 4 3 5 9

95% Confidence Interval
for Mean

Lower Bound 22.597

Upper Bound 24.314

5% Trimmed Mean 23.175

Median 23.085

Variance 47.877

Std. Deviation 6.9193

Minimum 5 . 5

Maximum 4 8 . 4

Range 4 3 . 0

Interquartile Range 9 . 2

Skewness . 5 8 7 . 1 5 3

Kurtosis . 5 5 9 . 3 0 6

WAISTHIPRATIO Mean . 9 2 4 5 .00372

95% Confidence Interval
for Mean

Lower Bound . 9 1 7 2

Upper Bound . 9 3 1 9

5% Trimmed Mean . 9 2 3 5

Median . 9 2 0 2

Variance . 0 0 3

Std. Deviation .05905

Minimum . 7 9

Maximum 1 . 1 0

Range . 3 1

Interquartile Range . 0 8

Skewness . 2 2 8 . 1 5 3

Kurtosis – . 1 6 5 . 3 0 6

Percentiles

Page 10

Percentiles

5 1 0 2 5 5 0 7 5 9 0 9 5

Weighted Average
(Definition 1)

BODYFAT 6 . 6 9 5 8 . 7 3 0 12.800 19.000 24.600 29.040 31.435

AGE 2 5 . 0 0 2 7 . 0 0 3 5 . 2 5 4 3 . 0 0 5 4 . 0 0 6 3 . 7 0 6 7 . 3 5

HEIGHT 136.0750 146.2250 158.5000 176.5000 197.0000 217.0000 227.1000

WEIGHT 65.7500 67.0000 68.2500 70.0000 72.2500 73.7500 74.5000

NECK 34.165 35.100 36.400 38.000 39.475 40.970 41.900

CHEST 88.765 90.890 94.250 99.650 105.525 112.370 117.175

ABDOMEN 76.565 79.430 84.525 90.950 99.575 105.910 111.305

HIP 89.065 91.800 95.500 99.300 103.575 108.800 112.540

THIGH 51.030 52.930 56.000 59.000 62.450 66.000 68.670

BICEPS 27.500 28.630 30.200 32.050 34.375 36.340 37.200

BMI 13.618 15.255 18.535 23.085 27.735 32.081 36.621

WAISTHIPRATIO . 8 3 1 6 . 8 4 7 0 . 8 8 6 0 . 9 2 0 2 . 9 6 3 4 1.0019 1.0309

Tukey’s Hinges BODYFAT 12.800 19.000 24.600

AGE 3 5 . 5 0 4 3 . 0 0 5 4 . 0 0

HEIGHT 158.7500 176.5000 197.0000

WEIGHT 68.2500 70.0000 72.2500

NECK 36.400 38.000 39.450

CHEST 94.300 99.650 105.450

ABDOMEN 84.550 90.950 99.450

HIP 95.500 99.300 103.550

THIGH 56.000 59.000 62.400

BICEPS 30.200 32.050 34.350

BMI 18.540 23.085 27.730

WAISTHIPRATIO . 8 8 6 0 . 9 2 0 2 . 9 6 3 3

Page 11

Extreme Values

1 8 2 118.50

Case Number Value

BODYFAT Highest 1 2 1 6 4 5 . 1

2 3 6 3 8 . 2

3 1 9 2 3 6 . 5

4 1 6 9 3 4 . 7

5 3 9 3 3 . 8

Lowest 1 1 8 2 . 0

2 1 7 2 1 . 9

3 1 7 1 4 . 1

4 2 6 4 . 6

5 2 9 4 . 7

AGE Highest 1 7 9 8 1

2 2 5 2 7 4

3 8 5 7 2

4 8 7 7 2

5 2 4 9 7 2a

Lowest 1 3 2 2

2 2 2 2

3 1 4 5 2 3

4 1 4 4 2 3

5 1 0 2 3b

HEIGHT Highest 1 3 9 363.15

2 4 1 262.75

3 3 5 247.25

4 1 9 2 244.25

5 1 5 2 241.75

Extreme Values

HEIGHT

3 9 1 3 6 . 2
Page 12

Case Number Value

Lowest 1 1 8 2 118.50

2 7 4 125.00

3 4 5 125.25

4 1 7 2 125.75

5 2 2 6 126.50

WEIGHT Highest 1 9 6 7 7 . 7 5

2 1 4 5 7 7 . 5 0

3 1 2 7 6 . 0 0

4 1 9 2 7 6 . 0 0

5 1 0 9 7 5 . 5 0

Lowest 1 4 2 2 9 . 5 0

2 2 1 6 6 4 . 0 0

3 7 4 6 4 . 0 0

4 2 9 6 4 . 7 5

5 3 6 6 5 . 0 0

NECK Highest 1 3 9 5 1 . 2

2 1 6 8 4 3 . 9

3 4 1 4 3 . 2

4 1 8 0 4 2 . 8

5 2 2 2 4 2 . 5

Lowest 1 1 0 6 3 1 . 1

2 4 5 3 1 . 5

3 4 9 3 2 . 8

4 7 4 3 3 . 2

5 2 2 6 3 3 . 4

Page 13

Extreme Values

1 8 2 8 5 . 0

Case Number Value

CHEST Highest 1 3 9 1 3 6 . 2

2 4 1 1 2 8 . 3

3 2 0 5 1 2 1 . 6

4 2 2 2 1 1 9 . 9

5 2 1 6 1 1 9 . 8

Lowest 1 1 8 2 7 9 . 3

2 5 0 8 3 . 4

3 4 5 8 5 . 1

4 2 3 8 6 . 0

5 2 4 8 6 . 7

ABDOMEN Highest 1 3 9 1 4 8 . 1

2 4 1 1 2 6 . 2

3 2 1 6 1 2 2 . 1

4 2 4 2 1 1 8 . 0

5 1 6 9 1 1 5 . 9

Lowest 1 1 8 2 6 9 . 4

2 5 0 7 0 . 4

3 1 5 3 7 2 . 8

4 4 7 7 3 . 7

5 2 9 7 3 . 9

HIP Highest 1 3 9 1 4 7 . 7

2 4 1 1 2 5 . 6

3 3 5 1 1 6 . 1

4 4 2 1 1 5 . 5

5 1 5 2 1 1 4 . 4 c

Extreme Values

HIP

1 8 2 4 8 . 4
Page 14

Case Number Value

Lowest 1 1 8 2 8 5 . 0

2 2 7 8 5 . 3

3 5 0 8 7 . 2

4 2 2 6 8 7 . 5

5 2 4 1 8 7 . 6

THIGH Highest 1 3 9 8 7 . 3

2 1 6 9 7 4 . 4

3 1 5 2 7 2 . 9

4 4 1 7 2 . 5

5 3 5 7 1 . 2 d

Lowest 1 1 8 2 4 7 . 2

2 5 3 4 9 . 3

3 2 4 8 4 9 . 6

4 1 7 2 5 0 . 0

5 4 5 5 0 . 0

BICEPS Highest 1 3 9 4 5 . 0

2 1 8 0 3 9 . 1

3 5 4 3 8 . 5

4 1 5 2 3 8 . 5

5 2 2 2 3 8 . 4

Lowest 1 1 7 2 2 4 . 8

2 2 2 6 2 5 . 3

3 2 4 8 2 5 . 6

4 1 4 9 2 5 . 8

5 5 1 2 6 . 0

Extreme Values

Page 15

Case Number Value

BMI Highest 1 1 8 2 4 8 . 4

2 4 5 4 3 . 4

3 2 2 6 4 1 . 7

4 1 7 2 4 1 . 4

5 5 0 4 1 . 1

Lowest 1 3 9 5 . 5

2 4 2 7 . 0

3 4 1 1 0 . 0

4 3 5 1 2 . 0

5 1 7 8 1 2 . 3

WAISTHIPRATIO Highest 1 2 5 0 1 . 1 0

2 5 9 1 . 0 9

3 2 1 6 1 . 0 8

4 2 0 5 1 . 0 6

5 4 0 1 . 0 5

Lowest 1 1 9 9 . 7 9

2 2 5 . 8 0

3 1 5 3 . 8 0

4 5 0 . 8 1

5 2 3 . 8 1

a. Only a partial list of cases with the value 72 are shown in the table of upper extremes.

b. Only a partial list of cases with the value 23 are shown in the table of lower extremes.

c. Only a partial list of cases with the value 114.4 are shown in the table of upper extremes.

d. Only a partial list of cases with the value 71.2 are shown in the table of upper extremes.

Scatter Graph Matrix f o r variables i n analysis

Notes

Output Created 20-SEP-2017 14:22:12

Comments

Input Data /Users/Rick/Desktop/PU
B4009/spss/FAT.sav

Active Dataset DataSet1

Filter < n o n e >

Weight < n o n e >

Split File < n o n e >

N of Rows in Working
Data File

2 5 2

Syntax GRAPH
/SCATTERPLOT
(MATRIX)=BODYFAT
HEIGHT WEIGHT NECK
CHEST ABDOMEN HIP
THIGH BICEPS BMI
WAISTHIPRATIO
AGE
/MISSING=LISTWISE.

Resources Processor Time 00:00:00.39

Elapsed Time 00:00:00.00

Page 16

Page 17

A
G

W
A

IS
T

H
IP

R
A

T
IO

B
M

B
IC

E
P

T
H

IG
H

H
IP

A
B

D
O

M
E

C
H

E
S

N
E

C
K

W
E

IG
H

H
E

IG
H

B
O

D
Y

F
A

B
M

I
H

IP
N

E
C

K
B

O
D

Y
F

A
T

Correlations Pearson

Notes

Output Created 20-SEP-2017 14:22:44

Comments

Input Data /Users/Rick/Desktop/PU
B4009/spss/FAT.sav

Active Dataset DataSet1

Filter < n o n e >

Weight < n o n e >

Split File < n o n e >

N of Rows in Working
Data File

2 5 2

Missing Value Handling Definition of Missing User-defined missing
values are treated as
missing.

Cases Used Statistics for each pair of
variables are based on
all the cases with valid
data for that pair.

Syntax CORRELATIONS
/VARIABLES=BODYFAT
HEIGHT WEIGHT NECK
CHEST ABDOMEN HIP
THIGH BICEPS BMI
WAISTHIPRATIO AGE
/PRINT=TWOTAIL
NOSIG
/MISSING=PAIRWISE.

Resources Processor Time 00:00:00.02

Elapsed Time 00:00:00.00

Page 18

. 4 9 3 * *

. 0 0 0

2 5 2

. 8 0 0 * *

. 0 0 0

2 5 2

. 2 0 8 * *

. 0 0 1

2 5 2

. 7 3 1 * *

. 0 0 0

2 5 2

. 7 2 8 * *

. 0 0 0

2 5 2

. 6 8 5 * *

. 0 0 0

2 5 2

. 7 3 9 * *

. 0 0 0

2 5 2

. 7 6 1 * *

. 0 0 0

2 5 2

. 4 9 3 . 8 0 0 . 2 0 8 . 7 3 1 . 7 2 8 . 6 8 5 . 7 3 9 . 7 6 1 1
Page 19

Correlations

BODYFAT

HEIGHT

WEIGHT

NECK

CHEST

ABDOMEN

HIP

THIGH

Pearson Correlation

BODYFAT

HEIGHT

. 6 1 3 * *
WEIGHT NECK

– . 0 8 9 . 4 9 1 * *
CHEST

. 7 0 3 * *
ABDOMEN

. 8 1 4 * *
HIP

. 6 2 6 * *
THIGH

. 5 6 1 * *

Sig. (2-tailed) . 0 0 0 . 1 5 8 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

Pearson Correlation . 6 1 3 * * 1 . 3 0 8 * * . 8 3 1 * * . 8 9 4 * * . 8 8 8 * * . 9 4 1 * * . 8 6 9 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

Pearson Correlation – . 0 8 9 . 3 0 8 * * 1 . 2 5 4 * * . 1 3 5 * . 0 8 8 . 1 7 0 * * . 1 4 8 *

Sig. (2-tailed) . 1 5 8 . 0 0 0 . 0 0 0 . 0 3 2 . 1 6 5 . 0 0 7 . 0 1 8

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

Pearson Correlation . 4 9 1 * * . 8 3 1 * * . 2 5 4 * * 1 . 7 8 5 * * . 7 5 4 * * . 7 3 5 * * . 6 9 6 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

Pearson Correlation . 7 0 3 * * . 8 9 4 * * . 1 3 5 * . 7 8 5 * * 1 . 9 1 6 * * . 8 2 9 * * . 7 3 0 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 3 2 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

Pearson Correlation . 8 1 4 * * . 8 8 8 * * . 0 8 8 . 7 5 4 * * . 9 1 6 * * 1 . 8 7 4 * * . 7 6 7 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 1 6 5 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

Pearson Correlation . 6 2 6 * * . 9 4 1 * * . 1 7 0 * * . 7 3 5 * * . 8 2 9 * * . 8 7 4 * * 1 . 8 9 6 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 7 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

Pearson Correlation . 5 6 1 * * . 8 6 9 * * . 1 4 8 * . 6 9 6 * * . 7 3 0 * * . 7 6 7 * * . 8 9 6 * * 1

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 1 8 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2
* * * * * * * * * * * * * * * *

1 – . 7 8 1 . 4 1 3 – . 0 4 1
Page 20

Correlations

WAISTHIPRATI

BODYFAT Pearson Correlation

BICEPS

. 4 9 3 * *
BMI

– . 6 6 8 * *
O

. 7 7 4 * *
AGE

. 2 8 9 * *

. 0 0 0

2 5 2

– . 0 1 3

. 8 4 0

2 5 2

– . 1 7 2 * *

. 0 0 6

2 5 2

. 1 1 4

. 0 7 2

2 5 2

. 1 7 6 * *

. 0 0 5

2 5 2

. 2 3 0 * *

. 0 0 0

2 5 2

– . 0 5 0

. 4 2 6

2 5 2

– . 2 0 0 * *

. 0 0 1

2 5 2

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2

HEIGHT Pearson Correlation . 8 0 0 * * – . 9 3 0 * * . 5 4 7 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2

WEIGHT Pearson Correlation . 2 0 8 * * – . 2 0 4 * * – . 0 2 8

Sig. (2-tailed) . 0 0 1 . 0 0 1 . 6 5 7

N 2 5 2 2 5 2 2 5 2

NECK Pearson Correlation . 7 3 1 * * – . 7 8 5 * * . 5 4 1 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2

CHEST Pearson Correlation . 7 2 8 * * – . 8 7 5 * * . 7 2 5 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2

ABDOMEN Pearson Correlation . 6 8 5 * * – . 8 6 4 * * . 8 2 7 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2

HIP Pearson Correlation . 7 3 9 * * – . 8 8 1 * * . 4 5 1 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2

THIGH Pearson Correlation . 7 6 1 * * – . 8 4 4 * * . 3 8 1 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2
* *

2 5 2
* *

Page 21

2 5 2

– . 7 8 1 * *

. 0 0 0

2 5 2

. 4 1 3 * *

. 0 0 0

2 5 2

– . 0 4 1

. 5 1 5

2 5 2

Correlations

BICEPS Pearson Correlation

BODYFAT

. 4 9 3 * *
HEIGHT

. 8 0 0 * *
WEIGHT

. 2 0 8 * *
NECK

. 7 3 1 * *
CHEST

. 7 2 8 * *
ABDOMEN

. 6 8 5 * *
HIP

. 7 3 9 * *
THIGH

. 7 6 1 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 1 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

BMI Pearson Correlation – . 6 6 8 * * – . 9 3 0 * * – . 2 0 4 * * – . 7 8 5 * * – . 8 7 5 * * – . 8 6 4 * * – . 8 8 1 * * – . 8 4 4 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 1 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

WAISTHIPRATIO Pearson Correlation . 7 7 4 * * . 5 4 7 * * – . 0 2 8 . 5 4 1 * * . 7 2 5 * * . 8 2 7 * * . 4 5 1 * * . 3 8 1 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 6 5 7 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

AGE Pearson Correlation . 2 8 9 * * – . 0 1 3 – . 1 7 2 * * . 1 1 4 . 1 7 6 * * . 2 3 0 * * – . 0 5 0 – . 2 0 0 * *

Sig. (2-tailed) . 0 0 0 . 8 4 0 . 0 0 6 . 0 7 2 . 0 0 5 . 0 0 0 . 4 2 6 . 0 0 1

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

Page 22

Correlations

WAISTHIPRATI

BICEPS Pearson Correlation

BICEPS

BMI

– . 7 8 1 * *
O

. 4 1 3 * *
AGE

– . 0 4 1

. 5 1 5

2 5 2

– . 0 2 3

. 7 1 5

2 5 2

. 4 7 9 * *

. 0 0 0

2 5 2

Sig. (2-tailed) . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2

BMI Pearson Correlation – . 7 8 1 * * 1 – . 5 9 0 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2

WAISTHIPRATIO Pearson Correlation . 4 1 3 * * – . 5 9 0 * * 1

Sig. (2-tailed) . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2

AGE Pearson Correlation – . 0 4 1 – . 0 2 3 . 4 7 9 * *

Sig. (2-tailed) . 5 1 5 . 7 1 5 . 0 0 0

N 2 5 2 2 5 2

* * . Correlation is significant at the 0.01 level (2-tailed).

2 5 2

* . Correlation is significant at the 0.05 level (2-tailed).

Nonparametric Correlations Spearman

Page 23

Notes

Output Created 20-SEP-2017 14:22:44

Comments

Input Data /Users/Rick/Desktop/PU
B4009/spss/FAT.sav

Active Dataset DataSet1

Filter < n o n e >

Weight < n o n e >

Split File < n o n e >

N of Rows in Working
Data File

2 5 2

Missing Value Handling Definition of Missing User-defined missing
values are treated as
missing.

Cases Used Statistics for each pair of
variables are based on
all the cases with valid
data for that pair.

Syntax NONPAR CORR
/VARIABLES=BODYFAT
HEIGHT WEIGHT NECK
CHEST ABDOMEN HIP
THIGH BICEPS BMI
WAISTHIPRATIO AGE
/PRINT=SPEARMAN
TWOTAIL NOSIG
/MISSING=PAIRWISE.

Resources Processor Time 00:00:00.03

Elapsed Time 00:00:00.00

Number of Cases Allowed 209715 cases a

a. Based on availability of workspace memory

Correlations

Spearman’s rho BODYFAT Correlation Coefficient

BODYFAT HEIGHT

1 . 0 0 0 . 6 1 3 * *
WEIGHT

– . 0 0 8

NECK

. 4 9 1 * *
CHEST

. 6 7 3 * *
ABDOMEN

. 8 1 5 * *
HIP

. 6 1 2 * *

Sig. (2-tailed) . . 0 0 0 . 8 9 8 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

HEIGHT Correlation Coefficient . 6 1 3 * * 1 . 0 0 0 . 5 1 5 * * . 8 0 5 * * . 8 9 7 * * . 8 7 4 * * . 9 2 9 * *

Sig. (2-tailed) . 0 0 0 . . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

WEIGHT Correlation Coefficient – . 0 0 8 . 5 1 5 * * 1 . 0 0 0 . 3 2 1 * * . 2 5 8 * * . 2 1 9 * * . 4 2 1 * *

Sig. (2-tailed) . 8 9 8 . 0 0 0 . . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

NECK Correlation Coefficient . 4 9 1 * * . 8 0 5 * * . 3 2 1 * * 1 . 0 0 0 . 7 8 2 * * . 7 4 3 * * . 7 0 9 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0 . . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

CHEST Correlation Coefficient . 6 7 3 * * . 8 9 7 * * . 2 5 8 * * . 7 8 2 * * 1 . 0 0 0 . 8 9 5 * * . 8 1 2 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

ABDOMEN Correlation Coefficient . 8 1 5 * * . 8 7 4 * * . 2 1 9 * * . 7 4 3 * * . 8 9 5 * * 1 . 0 0 0 . 8 4 5 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

HIP Correlation Coefficient . 6 1 2 * * . 9 2 9 * * . 4 2 1 * * . 7 0 9 * * . 8 1 2 * * . 8 4 5 * * 1 . 0 0 0

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 .

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

THIGH Correlation Coefficient . 5 4 4 * * . 8 3 7 * * . 3 3 3 * * . 6 4 9 * * . 7 2 0 * * . 7 3 4 * * . 8 7 8 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2
* * * * * * * * * * * * * *

. 5 4 4 * *

. 0 0 0

2 5 2

. 8 3 7 * *

. 0 0 0

2 5 2

. 3 3 3 * *

. 0 0 0

2 5 2

. 6 4 9 * *

. 0 0 0

2 5 2

. 7 2 0 * *

. 0 0 0

2 5 2

. 7 3 4 * *

. 0 0 0

2 5 2

. 8 7 8 * *

. 0 0 0

2 5 2

1 . 0 0 0

2 5 2

. 4 9 3 . 7 8 2 . 3 0 2 . 6 9 5 . 7 4 0 . 6 7 3 . 7 3 6 . 7 3 6 * *

Page 24

. 7 3 6 1 . 0 0 0 – . 7 9 4 . 4 3 8 – . 0 4 4
Page 25

Correlations

Spearman’s rho BODYFAT Correlation Coefficient

THIGH BICEPS

. 5 4 4 * * . 4 9 3 * *
BMI

– . 6 5 4 * *

WAISTHIPRATI
O

. 7 7 2 * *
AGE

. 2 7 3 * *

. 0 0 0

2 5 2

– . 0 1 3

. 8 3 7

2 5 2

– . 2 3 0 * *

. 0 0 0

2 5 2

. 1 2 3

. 0 5 1

2 5 2

. 1 6 8 * *

. 0 0 8

2 5 2

. 2 2 1 * *

. 0 0 0

2 5 2

– . 0 7 2

. 2 5 5

2 5 2

– . 2 0 3 * *

. 0 0 1

2 5 2

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2

HEIGHT Correlation Coefficient . 8 3 7 * * . 7 8 2 * * – . 9 9 3 * * . 5 7 7 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2

WEIGHT Correlation Coefficient . 3 3 3 * * . 3 0 2 * * – . 4 2 0 * * – . 0 2 5

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0 . 6 9 1

N 2 5 2 2 5 2 2 5 2 2 5 2

NECK Correlation Coefficient . 6 4 9 * * . 6 9 5 * * – . 8 1 1 * * . 5 7 0 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2

CHEST Correlation Coefficient . 7 2 0 * * . 7 4 0 * * – . 9 2 0 * * . 7 2 2 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2

ABDOMEN Correlation Coefficient . 7 3 4 * * . 6 7 3 * * – . 9 0 0 * * . 8 5 8 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2

HIP Correlation Coefficient . 8 7 8 * * . 7 3 6 * * – . 9 3 1 * * . 4 7 6 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2

THIGH Correlation Coefficient 1 . 0 0 0 . 7 3 6 * * – . 8 4 9 * * . 3 9 4 * *

Sig. (2-tailed) . . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2
* *

2 5 2 2 5 2
* *

2 5 2
* *

Correlations

BICEPS

BMI

WAISTHIPRATIO

AGE

Correlation Coefficient

BODYFAT HEIGHT

. 4 9 3 * * . 7 8 2 * *
WEIGHT

. 3 0 2 * *
NECK

. 6 9 5 * *
CHEST

. 7 4 0 * *
ABDOMEN

. 6 7 3 * *
HIP

. 7 3 6 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

Correlation Coefficient – . 6 5 4 * * – . 9 9 3 * * – . 4 2 0 * * – . 8 1 1 * * – . 9 2 0 * * – . 9 0 0 * * – . 9 3 1 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

Correlation Coefficient . 7 7 2 * * . 5 7 7 * * – . 0 2 5 . 5 7 0 * * . 7 2 2 * * . 8 5 8 * * . 4 7 6 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 6 9 1 . 0 0 0 . 0 0 0 . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

Correlation Coefficient . 2 7 3 * * – . 0 1 3 – . 2 3 0 * * . 1 2 3 . 1 6 8 * * . 2 2 1 * * – . 0 7 2

Sig. (2-tailed) . 0 0 0 . 8 3 7 . 0 0 0 . 0 5 1 . 0 0 8 . 0 0 0 . 2 5 5

N 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2 2 5 2

Spearman’s rho

. 7 3 6 * *

. 0 0 0

2 5 2

– . 8 4 9 * *

. 0 0 0

2 5 2

. 3 9 4 * *

. 0 0 0

2 5 2

– . 2 0 3 * *

. 0 0 1

2 5 2

Page 26

Page 27

Spearman’s rho

Correlations

BICEPS Correlation Coefficient

THIGH BICEPS

. 7 3 6 * * 1 . 0 0 0

BMI

– . 7 9 4 * *

WAISTHIPRATI
O

. 4 3 8 * *
AGE

– . 0 4 4

. 4 8 6

2 5 2

– . 0 1 4

. 8 2 9

2 5 2

. 4 5 3 * *

. 0 0 0

2 5 2

1 . 0 0 0

2 5 2

Sig. (2-tailed) . 0 0 0 . . 0 0 0 . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2

BMI Correlation Coefficient – . 8 4 9 * * – . 7 9 4 * * 1 . 0 0 0 – . 6 1 5 * *

Sig. (2-tailed) . 0 0 0 . 0 0 0 . . 0 0 0

N 2 5 2 2 5 2 2 5 2 2 5 2

WAISTHIPRATIO Correlation Coefficient . 3 9 4 * * . 4 3 8 * * – . 6 1 5 * * 1 . 0 0 0

Sig. (2-tailed) . 0 0 0 . 0 0 0 . 0 0 0 .

N 2 5 2 2 5 2 2 5 2 2 5 2

AGE Correlation Coefficient – . 2 0 3 * * – . 0 4 4 – . 0 1 4 . 4 5 3 * *

Sig. (2-tailed) . 0 0 1 . 4 8 6 . 8 2 9 . 0 0 0

* * . Correlation is significant at the 0.01 level (2-tailed).

2 5 2 2 5 2 2 5 2 2 5 2

Regression WEIGHT O N BODYFAT

Notes

Output Created 20-SEP-2017 15:35:59

Comments

Input Data /Users/Rick/Desktop/PU
B4009/spss/FAT.sav

Active Dataset DataSet1

Filter < n o n e >

Weight < n o n e >

Split File < n o n e >

N of Rows in Working
Data File

2 5 2

Missing Value Handling Definition of Missing User-defined missing
values are treated as
missing.

Cases Used Statistics are based on
cases with no missing
values for any variable
used.

Syntax REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF
OUTS CI(95) R ANOVA
/CRITERIA=PIN(.05)
POUT(.10)
/NOORIGIN
/DEPENDENT
BODYFAT
/METHOD=ENTER
WEIGHT.

Resources Processor Time 00:00:00.02

Elapsed Time 00:00:00.00

2848 bytes

Page 28

Page 29

Notes

Memory Required

Additional Memory
Required for Residual
Plots

2848 bytes

0 bytes

Resources

Variables Entered/Removed a

Variables Variables
Model Entered Removed Method

1 WEIGHTb . Enter

a. Dependent Variable: BODYFAT

b. All requested variables entered.

Model Summary

Adjusted R Std. Error of
Model R R Square Square the Estimate

1 . 0 8 9 a . 0 0 8 . 0 0 4 7.7354

a. Predictors: (Constant), WEIGHT

Page 30

ANOVAa

Model
Sum of
Squares df Mean Square F Sig.

1 Regression 119.727 1 119.727 2 . 0 0 1 . 1 5 8 b

Residual 14959.290 2 5 0 59.837

Total 15079.017 2 5 1

a. Dependent Variable: BODYFAT

b. Predictors: (Constant), WEIGHT

Coefficientsa

Unstandardized Coefficients
Standardized

Coefficients 95.0% Confidence Interval for B

Model B Std. Error Beta t Sig. Lower Bound Upper Bound

1 (Constant) 32.165 9 . 3 6 3 3 . 4 3 5 . 0 0 1 13.724 50.607

WEIGHT – . 1 8 9 . 1 3 3 – . 0 8 9 – 1 . 4 1 5 . 1 5 8 – . 4 5 1 . 0 7 4

a. Dependent Variable: BODYFAT

REGRESSION PLOT OF WEIGHT O N BODYFAT

Page 31

Notes

Output Created 20-SEP-2017 15:36:33

Comments

Input Data /Users/Rick/Desktop/PU
B4009/spss/FAT.sav

Active Dataset DataSet1

Filter < n o n e >

Weight < n o n e >

Split File < n o n e >

N of Rows in Working
Data File

2 5 2

Notes

Syntax GGRAPH
/GRAPHDATASET
NAME=”graphdataset”
VARIABLES= BODYFAT
WEIGHT
/GRAPHSPEC
SOURCE=INLINE.
BEGIN GPL
SOURCE: s=userSource
(id(“graphdataset”) )
DATA: BODYFAT = col
(source(s), name
(“BODYFAT”) )
GRAPH: begin(origin
(15%, 10%), scale(75%,
75%))
DATA: WEIGHT = col
(source(s), name
(“WEIGHT”) )
GUIDE: axis(dim(1),
label(“WEIGHT”) )
GUIDE: axis(dim(2),
label(“BODYFAT”) )
ELEMENT: point(position
(WEIGHT * BODYFAT) )
ELEMENT: line(position
(smooth.linear(WEIGHT *
BODYFAT)), shape
(shape.solid) )
GRAPH: end()
GRAPH: begin(origin
(15%, 0%), scale(75%,
8%))
GUIDE: axis(dim(1), ticks
(null()))
COORD: rect(dim(1))
ELEMENT: schema
(position(bin.quantile.
letter(WEIGHT)), size
(size.”80%”))
GRAPH: end()
GRAPH: begin(origin
(92%, 10%), scale(8%,
75%))
COORD: transpose(rect
(dim(1)))
GUIDE: axis(dim(1), ticks
(null()))
ELEMENT: schema
(position(bin.quantile.
letter(BODYFAT)), size
(size.”80%”))
GRAPH: end()
END GPL.

00:00:00.34

Page 32

Page 33

Notes

Resources Processor Time 00:00:00.34

Elapsed Time 00:00:01.00

WEIGHT

8 0 . 0 07 0 . 0 06 0 . 0 05 0 . 0 04 0 . 0 03 0 . 0 02 0 . 0 0

B
O

D
Y

F
A

5 0 . 0

4 0 . 0

3 0 . 0

2 0 . 0

1 0 . 0

. 0

Regression Abdomen on bodyfat

Notes

Output Created 20-SEP-2017 16:05:35

Comments

Input Data /Users/Rick/Desktop/PU
B4009/spss/FAT.sav

Active Dataset DataSet1

Filter < n o n e >

Weight < n o n e >

Split File < n o n e >

N of Rows in Working
Data File

2 5 2

Missing Value Handling Definition of Missing User-defined missing
values are treated as
missing.

Cases Used Statistics are based on
cases with no missing
values for any variable
used.

Syntax REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF
OUTS CI(95) R ANOVA
/CRITERIA=PIN(.05)
POUT(.10)
/NOORIGIN
/DEPENDENT
BODYFAT
/METHOD=ENTER
ABDOMEN.

00:00:00.01

Page 34

Page 35

Notes

Resources Processor Time 00:00:00.01

Elapsed Time 00:00:00.00

Memory Required 2848 bytes

Additional Memory
Required for Residual
Plots

0 bytes

Variables Entered/Removed a

Variables Variables
Model Entered Removed Method

1 ABDOMENb . Enter

a. Dependent Variable: BODYFAT

b. All requested variables entered.

Model Summary

Adjusted R Std. Error of
Model R R Square Square the Estimate

1 . 8 1 4 a . 6 6 2 . 6 6 1 4.5144

a. Predictors: (Constant), ABDOMEN

ANOVAa

Model
Sum of
Squares df Mean Square F Sig.

1 Regression 9984.086 1 9984.086 489.903 . 0 0 0 b

Residual 5094.931 2 5 0 20.380

Total 15079.017 2 5 1

a. Dependent Variable: BODYFAT

b. Predictors: (Constant), ABDOMEN

Page 36

Coefficientsa

Unstandardized Coefficients
Standardized

Coefficients 95.0% Confidence Interval for B

Model B Std. Error Beta t Sig. Lower Bound Upper Bound

1 (Constant) – 3 5 . 1 9 7 2 . 4 6 2 – 1 4 . 2 9 4 . 0 0 0 – 4 0 . 0 4 6 – 3 0 . 3 4 7

ABDOMEN . 5 8 5 . 0 2 6 . 8 1 4 22.134 . 0 0 0 . 5 3 3 . 6 3 7

a. Dependent Variable: BODYFAT

Regression Graph

Page 37

Notes

Output Created 20-SEP-2017 16:06:27

Comments

Input Data /Users/Rick/Desktop/PU
B4009/spss/FAT.sav

Active Dataset DataSet1

Filter < n o n e >

Weight < n o n e >

Split File < n o n e >

N of Rows in Working
Data File

2 5 2

Notes

Syntax GGRAPH
/GRAPHDATASET
NAME=”graphdataset”
VARIABLES= BODYFAT
ABDOMEN
/GRAPHSPEC
SOURCE=INLINE.
BEGIN GPL
SOURCE: s=userSource
(id(“graphdataset”) )
DATA: BODYFAT = col
(source(s), name
(“BODYFAT”) )
GRAPH: begin(origin
(15%, 10%), scale(75%,
75%))
DATA: ABDOMEN = col
(source(s), name
(“ABDOMEN”) )
GUIDE: axis(dim(1),
label(“ABDOMEN”) )
GUIDE: axis(dim(2),
label(“BODYFAT”) )
ELEMENT: point(position
(ABDOMEN * BODYFAT) )
ELEMENT: line(position
(smooth.linear
(ABDOMEN * BODYFAT)),
shape(shape.solid) )
GRAPH: end()
GRAPH: begin(origin
(15%, 0%), scale(75%,
8%))
GUIDE: axis(dim(1), ticks
(null()))
COORD: rect(dim(1))
ELEMENT: schema
(position(bin.quantile.
letter(ABDOMEN)), size
(size.”80%”))
GRAPH: end()
GRAPH: begin(origin
(92%, 10%), scale(8%,
75%))
COORD: transpose(rect
(dim(1)))
GUIDE: axis(dim(1), ticks
(null()))
ELEMENT: schema
(position(bin.quantile.
letter(BODYFAT)), size
(size.”80%”))
GRAPH: end()
END GPL.

00:00:00.23

Page 38

Page 39

Notes

Resources Processor …

Get Your Paper Before the Deadline. Our Services are 100% private and Confidential

Useful Links That Will Help You Around

Link to new order https://studentsolutionsusa.com/orders/stud/new

link to login page https://studentsolutionsusa.com/orders/login

New user registration link https://studentsolutionsusa.com/orders/register

Forgot Password https://studentsolutionsusa.com/orders/forgot/password

FREQUENTLY ASKED QUESTIONS

Question: How does this work?

Answer: Good Question. We are a group of a freelance board of students and professional essay writers. At our website, you may get help with any type of academic assignments: essay, coursework, term paper, business plan, case study, article review, research paper, presentation, and speech. Top writers can help with complex assignments such as dissertations, thesis papers, etc. All of them are professionals possessing excellent knowledge in their field of expertise, perfect writing skills, quality, and speed. When you place an order on our website, we assign it to the best writer. Once the writer finishes the work, the paper is submitted to our quality assurance desk who go through it and ensure it is unique and plagiarism free and that the instructions were followed to the detail. After this step we upload the paper in your account, we also send a copy to the email that you used to register the account with. we can guarantee you that the paper will be 100% plagiarism free. Besides, our services are 100% private and confidential

Question: How do I place an Order after getting to the order page

Answer: There are three major steps in the ordering process

Step 1 ....................................................paper details In this step, you will fill in the instructions of your paper; you can upload any materials that you feel will make your assignment a success. Besides, you can also email us at [email protected] Remember to specify the correct academic level. Please note that sources mean the number of references.

Step 2...................................................... Price calculation Kindly specify the number of pages, type of spacing and the correct deadline. This step will give you the estimated cost minus discount -- you may add the extra features if you wish.

Step 3 ....................................................discount and payment Use the discount code HAPPY2018 to enjoy up to 30% discount of your total cost After this step, proceed to safe payment; you can checkout using your card or PayPal Please note we will send the complete paper to the email you will provide while registering. A copy will also be uploaded to your account

Question: How will I know when my paper is complete? or How will I get the complete Paper?

Answer: Once we are done with the paper, we will be uploaded to your account. A copy will also be sent to the email you registered with. We can guarantee you the following:- 1. Our service is private and confidential; we don't spam or share your contacts with anyone 2. The final paper will be plagiarism free. We will send a Turnitin Report to the email you registered with 3. At our company, willing to do free unlimited revisions until you are satisfied with your paper

Question:- Am a new client, How can I get the guarantee that the paper will be completed and sent to me before my deadline?

Answer: Thank you for expressing your concerns. We would love to have you as our loyal customer. We are certain if we do good work, you will come back for me. Besides, you will give us referrals to your friends and family. For that reason, we can’t fail to deliver your paper within your specified time frame. We will ensure we submit the paper on time so that you can have enough time to go through it, if you have problems with the paper delivered, you can request a free revision. You are entitled to as many revisions as you would wish until you get a paper that satisfies you

Correlation and Simple Regression Tables Template Hypothesis Testing: Correlation and Simple Reg

u08a1 Correlation and Simple Regression Tables Template

Correlation Table

Report Results and Interpretation of Regression Analysis

Regression Analysis Table

Interpretation of Regression

Useful Links That Will Help You Around

FREQUENTLY ASKED QUESTIONS

Question: How does this work?

Question: How do I place an Order after getting to the order page

Question: How will I know when my paper is complete? or How will I get the complete Paper?

Question:- Am a new client, How can I get the guarantee that the paper will be completed and sent to me before my deadline?

Useful Links That Will Help You Around

Contact Us