Mathematics
QNT561 Phoenix Annual food spending & Household Income Analysis

QNT561

University of Phoenix

Question Description

Resources: Microsoft Excel®, Signature Assignment Databases, Signature Assignment Options, Part 3: Inferential Statistics

Scenario: Upon successful completion of the MBA program, say you work in the analytics department for a consulting company. Your assignment is to analyze one of the following databases:

• Manufacturing
• Hospital
• Consumer Food
• Financial

Select one of the databases based on the information in the Signature Assignment Options.

Provide a 1,600-word detailed, statistical report including the following:

• Explain the context of the case
• Provide a research foundation for the topic
• Present graphs
• Explain outliers
• Prepare calculations
• Conduct hypotheses tests
• Discuss inferences you have made from the results

This assignment is broken down into four parts:

• Part 1 - Preliminary Analysis
• Part 2 - Examination of Descriptive Statistics
• Part 3 - Examination of Inferential Statistics
• Part 4 - Conclusion/Recommendations

Part 1 - Preliminary Analysis (3-4 paragraphs)

Generally, as a statistics consultant, you will be given a problem and data. At times, you may have to gather additional data. For this assignment, assume all the data is already gathered for you.

State the objective:

• What are the questions you are trying to address?

Describe the population in the study clearly and in sufficient detail:

• What is the sample?

Discuss the types of data and variables:

• Are the data quantitative or qualitative?
• What are levels of measurement for the data?

Part 2 - Descriptive Statistics (3-4 paragraphs)

Examine the given data.

Present the descriptive statistics (mean, median, mode, range, standard deviation, variance, CV, and five-number summary).

Identify any outliers in the data.

Present any graphs or charts you think are appropriate for the data.

Note: Ideally, we want to assess the conditions of normality too. However, for the purpose of this exercise, assume data is drawn from normal populations.

Part 3 - Inferential Statistics (2-3 paragraphs)

Use the Part 3: Inferential Statistics document.

• Create (formulate) hypotheses
• Run formal hypothesis tests
• Make decisions. Your decisions should be stated in non-technical terms.

Hint: A final conclusion saying "reject the null hypothesis" by itself without explanation is basically worthless to those who hired you. Similarly, stating the conclusion is false or rejected is not sufficient.

Part 4 - Conclusion and Recommendations (1-2 paragraphs)

Include the following:

• What do you infer from the statistical analysis?
• State the interpretations in non-technical terms. What information might lead to a different conclusion?
• Are there any variables missing?
• What additional information would be valuable to help draw a more certain conclusion?

Format your assignment consistent with APA format.

Unformatted Attachment Preview

Purchase answer to see full attachment

Attached.

Signature Assignment-Data Analysis
Student’s Name
Institutional Affiliation

1

SIGNATURE ASSIGNMENT

2

1.0 Preliminary Analysis .............................................................................................................. 3
1.2 Study Questions ................................................................................................................... 4
1.3 Study Population ................................................................................................................. 4
1.4 Study Sample ....................................................................................................................... 4
1.5 Type of Data and Variable Measurement ......................................................................... 5
2.0 Descriptive Statistics ............................................................................................................... 5
3.0 Inference Statistic.................................................................................................................... 8
3.1 Hypothesis ............................................................................................................................ 8
3.2 Regression Models ............................................................................................................... 9
3.3 Results and Discussion ........................................................................................................ 9
4.0 Conclusion ............................................................................................................................. 12
4.1 Recommendations ................................................................................................................. 13

SIGNATURE ASSIGNMENT

3

Signature Assignment-Data Analysis
In the course of making informed decision data analysis is a paramount tool that assists in
establishing the suitability of a particular decision, for instance, in the process of determining
factors that influence an individual purchasing power. Worth a note, information analysis
involves the process of collecting, cleaning, manipulating as well as modeling information with a
desire of determining various discoveries as well as making different essential inferences in
supporting a particular decision (Gelman, Carlin, Stern, & Rubin, 2014). Besides, information
analysis could be utilized in the course of determining various associations among elements in a
study, which enables an analyst to make subtle conclusions between various relationships
depicted by variables. Therefore, in the process of making informed and supported
recommendations, it is indispensable to carry out a data analysis in the course of determining
different statistical associations between variables in a dataset.
1.0 Preliminary Analysis
Noteworthy, the disquisition entails an analysis of the annual food spending in the
consumer food data based on the household annual income, household non-mortgage debt in
comparison with the region as well as the location of the participants. Notably, different
descriptive, as well as inference analysis, would be conducted in the course of making inferences
related to the association of the variables on the consumer food information. Besides, regression
analysis will be utilized in the course of rejecting or accepting the research hypothetical
statements at an alpha level of 0.01.

SIGNATURE ASSIGNMENT
The primary objective of the study is to establish whether there exists an association between
regions in relation to the annual food spending, annual household income as well as the nonmortgage household debt.
Specific Objective
To determine if there is a significant difference between households in a metro area and
households outside metro areas in annual food spending.
1.2 Study Questions
I.
II.
III.

What is the association between the region and the annual food spending?
What is the association between the region and the annual household income?
What is the association between the region and the annual Non-mortgage household
debt?

IV.

What is the association between the Location and the annual food spending?

1.3 Study Population
Subsequently, a study population is a collection of individual or elements in a study that
reveals various common characteristics with binding similarities also referred as a research
cohort (Ritchie, Lewis, Nicholls, & Ormston, 2013). In the study, the population entailed a
cohort of individuals living in the four distinct regions of NE, MW, S, and W in the metro as
well as outside the metro locations in the consumer food dataset. Besides, the study utilized a
random sample since the information could not have been gathered from the entire population.
1.4 Study Sample
Notably, a sample is a manageable subset of a population selected to represent the entire
population (Marshall, Cardon, Poddar, & Fontenot, 2013). As a result, the research involves a

4

SIGNATURE ASSIGNMENT

5

sample population selected to represent the entire population in the region with a sample size N
200 respondents, who participated in the consumer food study.
1.5 Type of Data and Variable Measurement
Subsequently, there are two primary classifications of information either the quantitative
or qualitative data. Quantitative data entails the information presented in numerals in a study that
could be measured in various quantities while the qualitative information involves the narrative's
description in a research (Creswell, 2013). Therefore, the consumer food study utilized
quantitative data in all the variables of annual food spending, household income, non-mortgage
debts region as well as the location. On the other hand, annual food spending, household income,
and non-mortgage debts reveal ratio scale while the elements for the region is an ordinal and
location is classified as nominal variables. Notably, a ratio scale in element measurement entails
variables that stated based on a rational number zero and nominal variables reveals dichotomous
elements. Nonetheless, the ordinal elements comprise of various ranks, for instance, regions in
the data.
2.0 Descriptive Statistics
Notably, various descriptive statistics were determined in the desire of establishing
different measures of the central tendency as well as the measure of variation from the consumer
food data as shown in the table below.

SIGNATURE ASSIGNMENT

6

Table 1: Descriptive Statistic (N 200)
Annual Food Spending
(\$)

Annual Household Income
(\$)

Non-mortgage
household debt (\$)

Mean

8,966

55,552

15,604

Median

8,932

54,957

16,100

Mode

6,314

0

-

Maximum

17,740

96,132

36,374

Minimum

2,587

21,647

-

range

15,153

74,486

36,374

standard deviation

3,125

14,661

8,584

0.348537289

0

1

Quartile 1

6,934

46,163

9,192

Quartile 3

10,950

64,934

21,259

Coefficient of variance

Table 1 depicts the averages for annual food spending, annual household income and nonmortgage household debts as 8,966, 55,552 and 15,604 dollars respectively. Besides, the highest
amount spent on food was 17,740 dollars, and the maximum household income was 96,132
dollars while maximum recorded non-mortgage household debt amounted 36,374 dollars.
Besides, other five- number summary for the quartile 1 and quartile 2 reveals 6,934, 46,146 and
9,192 dollars in quartile 1 while 10,950, 64,934 and 21,259 for quartile 3, in food, spending
household income and non-mortgage debts respectively.
Table 2: Cross tabulation between Region and Location with aggregate food spending (N 200)
Sum of Annual Food Spending (\$)
Metro
MW
NE
S
W
Grand Total

276,343
394,144
161,071
300,754
1,132,312

Outside Metro
113,343
173,935
152,287
221,336
660,901

Grand Total
389,686
568,079
313,358
522,090
1,793,213

SIGNATURE ASSIGNMENT

7

Table 2 above reveals a cross tabulation between region and location with respect to the
aggregate annual food spending. Worth a note, Metro-west region depicted the highest total food
spending of 300,000 dollars, while outside Metro MW region revealed the least food spending
annually totaling to 113...

ephykam (8597)
Purdue University
Review

Anonymous
Return customer, been using sp for a good two years now.

Anonymous
Thanks as always for the good work!

Anonymous
Excellent job

Studypool
4.7
Trustpilot
4.5
Sitejabber
4.4

Brown University

1271 Tutors

California Institute of Technology

2131 Tutors

Carnegie Mellon University

982 Tutors

Columbia University

1256 Tutors

Dartmouth University

2113 Tutors

Emory University

2279 Tutors

Harvard University

599 Tutors

Massachusetts Institute of Technology

2319 Tutors

New York University

1645 Tutors

Notre Dam University

1911 Tutors

Oklahoma University

2122 Tutors

Pennsylvania State University

932 Tutors

Princeton University

1211 Tutors

Stanford University

983 Tutors

University of California

1282 Tutors

Oxford University

123 Tutors

Yale University

2325 Tutors