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 1,600word 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 (34 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 (34 paragraphs)
Examine the given data.
Present the descriptive statistics (mean, median, mode, range, standard deviation, variance, CV, and fivenumber 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 (23 paragraphs)
Use the Part 3: Inferential Statistics document.
 Create (formulate) hypotheses
 Run formal hypothesis tests
 Make decisions. Your decisions should be stated in nontechnical 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 (12 paragraphs)
Include the following:
 What are your conclusions?
 What do you infer from the statistical analysis?
 State the interpretations in nontechnical 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.
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Final Answer
Attached.
Running head: SIGNATURE ASSIGNMENT
Signature AssignmentData Analysis
Student’s Name
Institutional Affiliation
1
SIGNATURE ASSIGNMENT
2
Table of Contents
1.0 Preliminary Analysis .............................................................................................................. 3
1.1 Broad Objective ................................................................................................................... 4
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 AssignmentData 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 nonmortgage 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
1.1 Broad Objective
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 Nonmortgage 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
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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, nonmortgage
debts region as well as the location. On the other hand, annual food spending, household income,
and nonmortgage 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
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Table 1: Descriptive Statistic (N 200)
Annual Food Spending
($)
Annual Household Income
($)
Nonmortgage
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 nonmortgage 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 nonmortgage 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
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Table 2 above reveals a cross tabulation between region and location with respect to the
aggregate annual food spending. Worth a note, Metrowest 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...
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