PA 3010 Central Washington University Central Tendency and Variability Worksheet

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Mathematics

PA 3010

Central Washington University

PA

Description

Requirement

• This assignment should be completed in Word. However, you are required to record your statistical analysis in Excel with formulas or functions kept inside. In other words, you need to submit two files (Word and Excel) to me for grading. This is required since I want to make sure you clearly know how to run formulas or functions in Excelto conduct the statistical analysis, which is a core purpose for this course.

Content

The ongoing pandemic provides us with a proper scenario where the relationship between politics, public health crisis, and economic development can be investigated. The given data set includes the confirmed cases of COVID-19 every 100,000 people (case rate per 100,000) and the gross domestic product (GDP) per capita as of 2020 in three groups of states with different political affiliation (swing states, solid red states, and solid blue states). In this context, case rate per 100,000 and GDP per capita in 2020 are two relative strength indicators taking population size into consideration. Compared with the absolute strength indicators (total confirmed cases and GDP), the relative strength ones can best represent the status quo of public health crisis and economic development, enabling a valuable comparative analysis across states. Specifically, the given data set is used to answer the following questions:

• Calculate and compare central tendency and variability of case rate per 100,000 and GDP per capita in 2020 among swing, solid blue, and solid red states.
• Please write out your observations and comments attached behind the below table regarding the comparison of confirmed cases of COVID-19 and economic development among swing, solid blue, and solid red states. For example, do swing states, on average, have more (or less) confirmed cases of COVID-19 and better (or worse) economic development than solid red and solid blue states? Are these observations or findings attractive to you? How will you justify these observations or findings? (Notes: Complete it in Word.)
• Insert a new sheet in the given data set to place the new grouped data by political affiliation and case rate per 100,000. (Notes: Complete it in Excel.)
• Follow the famous eight steps to test the hypothesis above. (Notes: Notes: Complete it in Word.)
• Use the flowchart in textbook to select the most appropriate test statistic to examine whether the means of case rate per 100,000 among three groups of states (swing states, solid red states, and solid blue states) are different.
• The ongoing pandemic brings up two critical questions requiring further examination. First, whether is there a relationship between the confirmed cases of COVID-19 (case rate per 100,000) and economic development (GDP per capita in 2020)? Second, the degree to which have the confirmed cases of COVID-19 (case rate per 100,000) affected economic development (GDP per capita in 2020)? The given sample data (24 states) will be used to answer the above two questions.
• Use the correlation coefficient to examine the first question. You are NOT required to follow the famous eight steps to conduct the test statistic. Instead, you can use “Data Analysis Tools” in Excel to calculate the correlation. (Notes: Complete it in Excel.) (). However, you are REQUIRED to interpret and evaluate the correlation coefficient using “Thumb Rule”, “Coefficient of Determination”, and “Association versus Causality”. (Notes: Complete it in Word.) (
• Use the regression analysis to examine the second question. Again, you are NOT required to follow the famous eight steps to conduct the test statistic. Instead, you can use “Data Analysis Tools” in Excel to get a regression equation or line that can reflect how the confirmed cases of COVID-19 (case rate per 100,000) affects economic development (GDP per capita in 2020). (Notes: Complete it in Excel.) (2 pts). However, you are REQUIRED to clearly and precisely state the independent variable, the dependent variable, slope and intercept, the regression equation, and a scatterplot that can visualize how the confirmed cases of COVID-19 (case rate per 100,000) affects economic development (GDP per capita in 2020). Finally, please calculate the predicted GDP per capita when the case rate per 100,000 goes up to 15,000. (Notes: Complete it in Word)

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View attached explanation and answer. Let me know if you have any questions.😀 Hi there! I completed the assignment! 😀 I'm aiming to be a 5 starts tutor, hence feel free to send me any questions and to review what ever I did. I will be willing to fix it asap.

Political Affiliation

State

Case Rate per
100,000

GDP Per
Capita in
2020 (\$)

Arizona
11.702
50.187
Florida
9.815
50.424
Georgia
10.172
57.819
Michigan
8.589
51.766
Swing States
10.055
54.998
North Carolina
8.974
55.292
Pennsylvania
8.537
61.031
Wisconsin
11.150
58.066
Arkansas
11.033
42.591
Indiana
10.447
55.165
Kansas
10.480
59.475
Kentucky
9.753
46.909
Solid Red States
11.156
66.480
Oklahoma
11.242
46.871
Tennessee
12.141
52.925
Wyoming
9.884
62.236
California
9.134
78.538
8.428
67.169
Connecticut
9.200
78.971
Delaware
10.261
76.522
Solid Blue States
Maryland
7.194
69.805
Massachusetts
9.234
84.722
New Jersey
10.892
69.695
Virginia
7.536
64.229
Data Source: https://covid.cdc.gov/covid-data-tracker; U.S. Bureau of
Economic Analysis

Row Labels
Average of Case Rate per 100,000 StdDev of Case Rate per 100,000
Solid Blue States
8985
1254
Solid Red States
10767
786
Swing States
9874
1155
Grand Total
9875
1275

Average of GDP Per Capita in 2020 (\$) StdDev of GDP Per Capita in 2020 (\$)
\$ 73.706,38
\$ 7.012,26
\$ 54.081,50
\$ 8.343,41
\$ 54.947,88
\$ 3.934,23
\$ 60.911,92
\$ 11.242,81

Swing States Solid Red States Solid Blue States
11.702
11.033
9.134
9.815
10.447
8.428
10.172
10.480
9.200
8.589
9.753
10.261
10.055
11.156
7.194
8.974
11.242
9.234
8.537
12.141
10.892
11.150
9.884
7.536

Anova: Single Factor
SUMMARY
Groups
Swing States
Solid Red States
Solid Blue States

Count
8
8
8

ANOVA
Source of Variation
Between Groups
Within Groups

SS
12703893
24684614

Total

37388508

Sum
78994
86136
71879

df
2
21
23

Average
9874
10767
8985

Variance
1334799,9
618318,9
1573254,7

MS
6351946,63
1175457,83

F
5,4038

P-value
0,0128

F crit
3,4668

Political Affiliation

State
Arizona
Florida

GDP Per
Case Rate per
Capita in
100,000
2020 (\$)
11.702
50.187
9.815

50.424

Georgia
10.172
57.819
Michigan
8.589
51.766
Swing States
10.055
54.998
North Carolina
8.974
55.292
Pennsylvania
8.537
61.031
Wisconsin
11.150
58.066
Arkansas
11.033
42.591
Indiana
10.447
55.165
Kansas
10.480
59.475
Kentucky
9.753
46.909
Solid Red States
11.156
66.480
Oklahoma
11.242
46.871
Tennessee
12.141
52.925
Wyoming
9.884
62.236
California
9.134
78.538
8.428
67.169
Connecticut
9.200
78.971
Delaware
10.261
76.522
Solid Blue States
Maryland
7.194
69.805
Massachusetts
9.234
84.722
New Jersey
10.892
69.695
Virginia
7.536
64.229
Data Source: https://covid.cdc.gov/covid-data-tracker; U.S.
Bureau of Economic Analysis

Case Rate per 100,000
GDP Per Capita in 2020 (\$)

Coefficient of determination

Case Rate per 100,000

1
-0,388037299
0,150572946

GDP Per Capita in 2020 (\$)

1

Political Affiliation

Swing States

Solid Red States

Solid Blue States

State

GDP Per
Case Rate per
Capita in
100,000
2020 (\$)

Arizona

11.702

50.187

Florida

9.815

50.424

Georgia

10.172

57.819

Michigan

8.589

51.766

10.055

54.998

North Carolina

8.974

55.292

Pennsylvania

8.537

61.031

Wisconsin

11.150

58.066

Arkansas
Indiana
Kansas
Kentucky
Oklahoma
Tennessee
Wyoming
California

11.033
10.447
10.480
9.753
11.156
11.242
12.141
9.884
9.134

42.591
55.165
59.475
46.909
66.480
46.871
52.925
62.236
78.538

8.428

67.169

Connecticut

9.200

78.971

Delaware

10.261

76.522

Maryland
7.194
69.805
Massachusetts
9.234
84.722
New Jersey
10.892
69.695
Virginia
7.536
64.229
Data Source: https://covid.cdc.gov/covid-data-tracker; U.S.
Bureau of Economic Analysis

SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Standard Error
Observations
ANOVA
Regression
Residual
Total
Intercept
Case Rate per 100,000

For case rate per 100,000 = 15,000
43376,93718

Scatterplot
95.000
85.000

ession Statistics
0,3880
0,1506
0,1120
10594,7440
24

df
1
22
23

75.000

55.000
45.000
35.000
6.000

7.000

8.000

SS
MS
437748305 437748305
2469469213 112248601
2907217518

Coefficients Standard Error
94702,584
17247,11
-3,422
1,73

per 100,000 = 15,000

y = -3,4217x + 94703
R² = 0,1506

65.000

9.000

10.000 11.000 12.000 13.000

F
Significance F
3,8998
0,0610

t Stat
P-value
5,4909 0,0000
-1,9748 0,0610

Central tendency and variability
Below we...

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Anonymous
Just what I was looking for! Super helpful.

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