statistics signature assignment

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Signature Assignment, statistics homework help

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Mathematics

Description

Purpose of Assignment

The purpose of this assignment is for students to synthesize the concepts learned throughout the course. This assignment will provide students an opportunity to build critical thinking skills, develop businesses and organizations, and solve problems requiring data by compiling all pertinent information into one report.

Assignment Steps

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
• Consumer Food

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 are your conclusions?
• 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 with three references .

Unformatted Attachment Preview

Explanation & Answer

Attached. Running head: SIGNATURE ASSIGNMENT Signature Assignment- Information Analysis Student’s Name Institutional Affiliation 1 SIGNATURE ASSIGNMENT 2 Table of Contents 1.0 Preliminary Analysis .............................................................................................................. 3 1.1 Broad Objective ................................................................................................................... 3 1.2 Study Questions ................................................................................................................... 4 1.3 Study population ................................................................................................................. 4 1.4 Type of Data and Variable Measurement ......................................................................... 4 2.0 Descriptive Statistics ............................................................................................................... 5 3.0 Inference Statistic.................................................................................................................... 7 3.1 Hypothesis ............................................................................................................................ 7 3.2Regression model .................................................................................................................. 8 3.3 Results and Discussion ........................................................................................................ 8 4.0 Conclusion and Recommendation ....................................................................................... 11 SIGNATURE ASSIGNMENT 3 Signature Assignment- Information Analysis Information analysis is an imperative tool in the process of making informed decisions pertaining various aspects, for instance, in the course of estimating units of production as well as the cost of production. Worth a note, data analysis entails the process of gathering, cleaning, manipulating as well as modeling data in the desire of establishing discoveries and making various essential inferences that support a particular decision (Gelman, Carlin, Stern, & Rubin, 2014). Besides, information analysis could be utilized in the course of determining various associations among variables, which assists an analyst to make subtle deductions between various relationships revealed by variables in a study. Therefore, in the process of making sound and supported conclusions, it is imperative to carry out an information analysis in the desire of establishing various statistical associations between the data. 1.0 Preliminary Analysis Worth a note, the discourse entails an analysis of the consumer food information based on the household annual income, whether the household has non-mortgage household debt in comparison with the region as well as the location of the respondent. Notably, various descriptive, as well as inference analysis, would be conducted in the desire of making inferences related to the association of the available variables on the consumer food data. Besides, regression analysis will be utilized in the course of rejecting or accepting the research hypothetical statements. 1.1 Broad Objective The primary objective of the study is to establish the association between annual food spending in relation to annual income, non-mortgage debt as well as the location and region of the respondent. SIGNATURE ASSIGNMENT 4 Specific Objective To determine the association between a participant annual food spending and the household income and non-mortgage debts. 1.2 Study Questions 1. What is the relationship between the annual household income and the annual food spending? 2. What is the association between annual food spending and the respondent’s nonmortgage debt? 3. What is the relationship between annual food spending and the region of the respondent? 4. What is the association between annual food spending and the location of the participant? 1.3 Study Population Subsequently, a study population is a collection of persons that reveals various common and binding similarities (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. Besides, the study utilized a random sample since the information could not have been gathered from the entire population. 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 entails a sample population selected to represent the entire population in the region with a sample size N 200 respondents. 1.4 Type of Data and Variable Measurement Moreover, there are two primary classifications of data either quantitative or qualitative information. Quantitative data entails the data in numerals that could be measured in quantity SIGNATURE ASSIGNMENT 5 while qualitative information involves the narratives (Creswell, 2013). Thus, the 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 statistic was determined in the desire of establishing different measures of the central tendency as shown in the table below. Table 1: Descriptive Statistic (N 200) Annual Food Spending ($) Annual Household Income ($) Non-mortgage household debt ($) Mean 8,966 55,552 15,604 Median 8,932 54,957 16,100 Mode 6,314 #N/A - Maximum 17,740 96,132 36,374 Minimum 2,587 21,647 - range 15,153 74,486 36,374 standard deviation 3,125 14,661 8,584 0.348537289 0 1 Quartile 1 6,934 46,163 9,192 Quartile 3 10,950 64,934 21,259 Coefficient of variance Table 1 reveals means for annual food spending, annual household income and non-mortgage household debts as 8,966, 55,552 and 15,604 dollars respectively. Besides, the highest amount spent on food was 17,740 dollars, and the maximum household income was 96,132 dollars while SIGNATURE ASSIGNMENT 6 maximum recorded non-mortgage household debt amounted 36,374 dollars. Besides, other fivenumber summary for the quartile 1 and quartile 2 reveals 6,934, 46,146 and 9,192 dollars in quartile 1 while 10,950, 64,934 and 21,259 for quartile 3, in food, spending household income and non-mortgage debts respectively. Table 2: Cross tabulation between Region and Location with aggregate food spending (N 200) Sum of Annual Food Spending ($) Metro Outside Metro Grand Total MW 276,343 113,343 389,686 NE 394,144 173,935 568,079 S 161,071 152,287 313,358 W 300,754 221,336 522,090 1,132,312 660,901 1,793,213 Grand Total Table 2 above reveals a cross tabulation between region and location with respect to the aggregate annual food spending. Worth a note, Metro-we...

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