Practicing Application of Descriptive Statistics in Excel and SPSS

Practicing Application of Descriptive Statistics in Excel and SPSS
(1).Practicing Application of Descriptive Statistics in Excel and SPSS The purpose of this assignment is to compare basic functions in Excel and SPSS to calculate descriptive statistics and use this information to describe the sample.
For this assignment, students will utilize Excel with the Data Analysis ToolPak and SPSS Statistics and the ”Example Dataset” to complete the assignment. Refer to the Topic Materials for assistance with enabling the Data Analysis ToolPak on a Mac or PC.
Part 1:
Complete the following steps in both Excel and IBM SPSS Statistics.
Calculate mean, median, and mode for the variables ”Annual Income” and ”Age.” Show the appropriate summary tables for these measures from both Excel and SPSS. Include the other descriptive statistics that are a part of the summary output in Excel and SPSS. Practicing Application of Descriptive Statistics in Excel and SPSS
Create histograms to show the distribution for ”Annual Income” and ”Age.” Copy and paste the histograms from Excel and export the histogram from SPSS into the Word document for this assignment.
Create frequency tables that include counts and percentages for smoking status, employment status, exercise level, and education level. Show the tables in the Word document for this assignment.
Part 2:
Based upon the Part 1 activities, write a 250-500 word interpretation that addresses the following.
Discuss the sampling strategy used in this study and if it resulted in a representative sample.
Discuss what you are able to ascertain about the sample from the descriptive statistics.
Explain what other variables the research team could have included to gain a better understanding of the population.
General Requirements
Submit one Word document for the Part 1 assignment content and a second Word document for Part 2 of the assignment. Practicing Application of Descriptive Statistics in Excel and SPSS
APA style is not required, but solid academic writing is expected.
This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
You are not required to submit this assignment to LopesWrite.
(2).Calculating Confidence Intervals
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The purpose of this assignment is to practice calculating confidence intervals.
For this assignment, students will utilize Excel and SPSS Statistics and the ”Example Dataset.”
Using the ”Example Dataset,” complete the following:
Based on a normal distribution curve, calculate the probability of an individual being 60 years or older in this population. Show the Excel and SPSS formulas or your hand calculations. Include screenshots as needed to illustrate this.
Using the sample standard deviation of age as an estimate of the population standard deviation, calculate by hand the standard error of the mean. Show your calculations and the answer.
Calculate by hand a 95% confidence interval for ”Age” based on the sample mean. Use SPSS to verify your answer. Include your calculations and screenshots of the SPSS output.
Interpret the confidence interval for age and explain the three pieces of information needed to calculate a confidence interval.
Submit one Word document that includes all of the assignment deliverables.
APA style is not required, but solid academic writing is expected.
This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion. Practicing Application of Descriptive Statistics in Excel and SPSS
You are not required to submit this assignment to LopesWrite.
Practicing application of descriptive statistics
Part 1.
Calculating mean, median and mode for Annual Income and Age variables
 
Table 1. Excel output of descriptive statistics for age and annual income

Age
Annual_Income

Mean
39.93
34766.67

Standard Error
2.17
4176.48

Median
41.00
28000.00

Mode
42.00
28000.00

Standard Deviation
11.90
22875.50

Kurtosis
-0.79
-0.61

Skewness
-0.09
0.64

Range
43.00
80000.00

Minimum
18.00
5000.00

Maximum
61.00
85000.00

Sum
1198.00
1043000.00

Count
30.00
30.00

Confidence level (95.0%)
4.44
8541.85

 
Table 2. SPSS output of descriptive statistics for age and annual income Practicing Application of Descriptive Statistics in Excel and SPSS
 

Statistic
Std. Error

Age
Mean
39.93
2.173

95% Confidence Interval for Mean
Lower Bound
35.49

Upper Bound
44.38

5% Trimmed Mean
39.98

Median
41.00

Variance
141.651

Std. Deviation
11.902

Minimum
18

Maximum
61

Range
43

Interquartile Range
19

Skewness
-.091
.427

Kurtosis
-.791
.833

Annual_Income*
Mean
34766.67
4176.476

95% Confidence Interval for Mean
Lower Bound
26224.81

Upper Bound
43308.52

5% Trimmed Mean
33759.26

Median
28000.00

Variance
5.233E8

Std. Deviation
22875.500

Minimum
5000

Maximum
85000

Range
80000

Interquartile Range
37000

Skewness
.645
.427

Kurtosis
-.610
.833

 
 
Histogram for age and annual income
 
Figure 1. Excel output of histogram for age
 
Figure 2. Excel output of histogram for annual income
 
Figure 3. SPSS output of histogram for age
 
Figure 4. SPSS output of histogram for annual income
Frequency tables of counts and percentage for smoking status, employment status, exercise level, and education level
 
Table 3. Excel output of frequency tables for smoking status

Frequency
Percentage

No
18
60

Yes
12
40

 
Table 4. Excel output of frequency tables for education level

Frequency
Percentage

Less than high school
10
33.3

Graduated high school
10
33.3

Graduated college
10
33.3

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Table 5. Excel output of frequency tables for exercise level

Frequency
Percentage

0
1
3.3

20
1
3.3

25
1
3.3

40
2
6.7

45
1
3.3

50
5
16.7

60
2
6.7

65
3
10.0

70
1
3.3

75
2
6.7

80
4
13.3

90
1
3.3

100
1
3.3

110
2
6.7

120
1
3.3

150
1
3.3

200
1
3.3

 
Table 6. Excel output of frequency tables for employment status

Frequency
Percentage

No
13
43.3

Yes
17
56.7

 
Table 7. SPSS output of frequency tables for smoking status

Frequency
Percent
Valid Percent
Cumulative Percent

Valid
No
18
60.0
60.0
60.0

Yes
12
40.0
40.0
100.0

Total
30
100.0
100.0

 
Table 8. SPSS output of frequency tables for education level

Frequency
Percent
Valid Percent
Cumulative Percent

Valid
Less than high school
10
33.3
33.3
33.3

Graduated high school
10
33.3
33.3
66.7

Graduated college
10
33.3
33.3
100.0

Total
30
100.0
100.0

 
 
Table 9. SPSS output of frequency tables for exercise level

Frequency
Percent
Valid Percent
Cumulative Percent

Valid
0
1
3.3
3.3
3.3

20
1
3.3
3.3
6.7

25
1
3.3
3.3
10.0

40
2
6.7
6.7
16.7

45
1
3.3
3.3
20.0

50
5
16.7
16.7
36.7

60
2
6.7
6.7
43.3

65
3
10.0
10.0
53.3

70
1
3.3
3.3
56.7

75
2
6.7
6.7
63.3

80
4
13.3
13.3
76.7

90
1
3.3
3.3
80.0

100
1
3.3
3.3
83.3

110
2
6.7
6.7
90.0

120
1
3.3
3.3
93.3

150
1
3.3
3.3
96.7

200
1
3.3
3.3
100.0

Total
30
100.0
100.0

 
Table 10. Excel output of frequency tables for employment status

Frequency
Percent
Valid Percent
Cumulative Percent

Valid
No
13
43.3
43.3
43.3

Yes
17
56.7
56.7
100.0

Total
30
100.0
100.0

 
 
 
 
 
 
Part 2.
The analysis reveals that the participants had a mean age of 39.93 years and mean annual income of $34,766.67. A review of the collected data for age and annual income reveals that there is a 95% probability of the mean age of the population being between 35.49 years and 44.38 years. In addition, there is a 95% probability of the mean annual income of the population being between $26,224.82 and $43,308.52 (see Tables 1 & 2).
Although the sampling strategy has not been described, it resulted in a representative sample as indicated by the participants’ spread across the different demographic groups. All the age groups are well represented as shown in the bell-shaped chart for the histogram (see Figures 1 & 3). Still, the study would have recruited a better distribution of annual income as most of the participants earned less than the mean annual income (see Table 2 and Figures 2 & 4).  Further review of the smoking status reveals that 40% of the population are smokers while 60% are non-smokers (see Tables 3 & 7). A review of the education level reveals equal spread across the three education levels with 33.3% of the population having less than high school education, 33.3% having graduated from high school, and 33.3% graduated from college (see Tables 4 & 8). A review of the employment status reveals that 56.7% of the population is employed while 43.3% is unemployed (see Tables 6 & 10). In this respect, the demographic characteristics of the sample show that it is representative of the population with the different population characteristics well represented.
Other than the presented variables, the research team could have gained a better understanding of the population by collecting data on ethnicity and marital status as they have implications for health behavior. Ethnicity has implications for health behavior through genetics and cultural influences. Li et al. (2016) expounds on the influences of ethnicity by explaining that there is a need to develop culturally appropriate and evidence-based interventions to enhance healthy behavior among members of any population. Pandey et al. (2019) explains that marital status is both a cause and consequence of health behaviors through influencing economic well-being, and physical and mental health. In this respect, including ethnicity and marital status could help in gaining a better understanding of the general health behaviors of the population as well as relationships between health determinants. Practicing Application of Descriptive Statistics in Excel and SPSS.
 
 
Based on a normal distribution curve, calculate the probability of an individual being 60 years or older in this population.
The distribution of ages of the participants range from 18 years to 61 years. These ages are approximately normally distributed with a mean age of 39.93 years and a standard deviation of 11.9. The probability of a member of the population being 60 years of age or older is calculated as:
= NORM.DIST(60, 39.93, 11.9, TRUE) =  0.9542
Therefore, the probability of a member of the population being 60 years of age or older is:
= 1 – 0.9542 = 0.0458 or approximately 4.58%.
Using the sample standard deviation of age as an estimate of the population standard deviation, calculate by hand the standard error of the mean. Show your calculations and the answer.
Standard error = standard deviation / (√sample size) = 11.9 / √30 = 2.1726
Standard error = 2.17
The hand calculated figure for standard error of age matches the figures presented in the Excel output of the descriptive statistics for age (see Table 2).
Calculate by hand a 95% confidence interval for ”Age” based on the sample mean. Use SPSS to verify your answer. Include your calculations and screenshots of the SPSS output.
The sample has a mean age of 39.93 and standard error of 2.17. 95% confidence interval encompasses 95% of the area of the normal distribution, which is 1.96 standard deviations of the mean (z value). The confidence interval values are calculated as: Practicing Application of Descriptive Statistics in Excel and SPSS
Margin of error = z value * standard error = 1.96 * 2.17 = 4.25
Lower limit = 39.93 – 4.25 = 39.93 – 4.25 = 35.68
Upper limit = 39.93 + 4.25 = 39.93 + 4.25 = 44.18
95% CI (35.68, 44.18)
Interpret the confidence interval for age and explain the three pieces of information needed to calculate a confidence interval.
The hand calculated value is 95% CI (35.68, 44.18) while the value from the SPSS output is 95% CI (35.49, 44.38). The two values have slight differences at approximately 0.2. The difference is likely caused by approximations when making the hand calculations.
Three pierce of information were used to hand calculate the confidence interval. They included the z value, standard error and mean. Practicing Application of Descriptive Statistics in Excel and SPSS
 
 
References
Li, J., Thompson, T., Richards, T. & Steele, B. (2016). Racial and ethnic differences in health behaviors and preventive health services among prostate cancer survivors in the United States. Preventing Chronic Disease: Public Health Research, Practice, and Policy, 13, 160148. DOI: 10.5888/pcd13.160148
Pandey, K., Yang, F., Cagney, K., Smieliauskas, F., Meltzer, D. & Ruhnke, G. (2019). The impact of marital status on health care utilization among Medicare beneficiaries. Medicine, 98(12), e14871. DOI: 10.1097/MD.0000000000014871 Practicing Application of Descriptive Statistics in Excel and SPSS
 
 
 

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