Statistical Analyses Used. List the Statistical Procedures

¶ … statistical analyses used.

List the statistical procedures used to describe the sample.

Power analysis was used in order to discover power of effect. The power was set to 0.8 with a significant level of 0.05. Differences between the intervention and the control group were tested with Pearson's Chi. A t-test was used for the other perimeters. ANCOVA was used for testing changes between the two groups over time.

Was the level of significance or alpha identified? If so, indicate the level (.05, .01, or .001).

The level of significance was described. The power of the effect size was set to 0.8 with a significant level of 0.05. 0.05 was used throughout as perimeter of significance.

Complete the table below with the analysis techniques conducted in the study:

Identify the purpose (description, relationships, or differences) of each analysis technique.

Power analyses was used in order discover whether the test actually did discover a difference that did exist, in other words that the test avoided a Type II error and actually did record a statistical significance. For this reasons, one needs a significantly large enough population. 8 or greater is generally the power that is used, in other words that there is an 80% chance that one should find a statistically significant difference when there is one.

Pearson's Chi was used to test for distribution in sex, education (health care workers), current smoking status and musculoskeletal symptoms in neck, shoulders, upper- and lower back. It is used to test whether the observed frequency differs from the expected distribution. It also tests the independence, in other words in this case to test whether obesity of workers was connected with any of these factors or was independent of them.

A t-test was used for the other perimeters. A t-test is used to see whether difference exists between two groups. Here it was used to see whether difference existed between control and experiment group.

ANCOVA was used for testing changes between the two groups over time.

2) List the statistical procedures.

Power analysis was used in order to discover power of effect. The power was set to 0.8 with a significant level of 0.05. Differences between the intervention and the control group were tested with Pearson's Chi. A t-test was used for the other perimeters. ANCOVA was used for testing changes between the two groups over time. ANCOVA tests the variance in 2 or more groups taking into accounts possibility of variance of other factors.

3) List the statistics.

the intervention group significantly reduced body weight with 3.6 kg (p < 0.001), BMI from 30.5 to 29.2 (p < 0.001), body fat percentage from 40.9 to 39.3 (p < 0.001), waist circumference from 99.7 to 95.5 cm (p < 0.001) and blood pressure from 134/85 to 127/80 mmHg (p < 0.001), with significant difference between the intervention and control group (p < 0.001) on all measures.

4) Identify specific results.

The experimental group received a dietary plan with an energy deficit of 1200 kcal/day (15 min/hour), strengthening exercises (15 min/hour) and cognitive behavioral training (30 min/hour) during working hours 1 hour per week. Arabic fitness was also given for 2 hours per week. The control group was merely given monthly instruction. Body weight, BMI, body fat percentage (bioimpedance), waist circumference, blood pressure, musculoskeletal pain, maximal oxygen uptake (maximal bicycle test), and isometric maximal muscle strength of 3 body regions were measured at baseline and after the intervention period.

Results showed that there was significantly reduced body weight, body fat, waist circumference and blood pressure as well as increased aerobic fitness in the intervention group. This shows the benefit of promoting health amongst workplace employees. No effect of study was found in musculoskeletal pain, maximal oxygen uptake and muscle strength, but difference was found on aerobic fitness.

5) Provide specific probability value (p =) in a table as shown next.

Purpose of analysis

Statistical procedure

Statistic Result

Probability (p)

To assess difference in body weight

Pearson's Chi square

+0.68 (2.37)

0.000

To assess whether BMI would be reduced

Pearson's Chi square

+0.27 (0.85)

0.000

To assess reduction of body fat

Pearson's Chi square

+0.33 (1.25)

0.000

To assess difference in waist circumference

Pearson's Chi square

-0.91 (4.18)

p < 0.001

To assess difference in blood pressure

Pearson's Chi square

-0.68 (7.17)

-2.11 (9.25)

0.067

To assess difference in musculoskeletal pain

Pearson's Chi square

-0.24 (2.24)

-0.03 (1.54)

-0.11 (1.39)

+0.15 (1.99)

0.016

To assess difference in maximal oxygen uptake

Pearson's Chi square

+0.01 (0.21)

0.185

To assess difference in muscle strength

Pearson's Chi square

18.04 (34.46)

0.045

To assess difference in Aerobic fitness

Pearson's Chi square

-0.11 (2.87)

0.011

Comparison between experimental and control group t-test p < 0.001

12. Describe and critique the researcher's interpretation of findings.

a. What study limitations were identified by the researcher?

The lack of quantitative registration of physical training doses in leisure time. Also researcher admitted that it would have been better had each of the components been tested against their own control group but limited resources as well as time made this impossible.