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5 pages/≈1375 words
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APA
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Mathematics & Economics
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# Nike Research and Report Assignment Paper Part Two (Coursework Sample)

Instructions:

This is the second part of the previous paper that I have attached. Please base this paper off of the information from the one I've attached. ( or ref to # 00060035)
identify which types of descriptive statistics might be best for summarizing the data, if you were to collect a sample.
Analyze which types of inferential statistics might be best for analyzing the data, if you were to collect a sample.
Analyze the role probability or trend analysis might play in helping address the business problem.
Analyze the role linear regression for trend analysis might play in helping address the business problem.
Analyze the role a time series might play in helping address the business problem.
APA format.

source..
Content:

Nike Part Two
Student's Name
Institutional Affiliation
Nike Part Two
The business problem at Nike is a decline in sales due to various factors such as poor marketing strategies, changes in customer tastes and preferences and stiff competition from online stores like Amazon.com Inc. In part one, it was agreed that qualitative data to be used in analyzing the problem. The chosen methods allows data to be grouped into various categories which are considered necessary. Consequently, it was discovered that recognition of the factors leading to this problem be variable for solving the issue in Nike.
Identify which types of descriptive statistics might be best for summarizing the data, if you were to collect a sample.
Descriptive statistics provides a summary of the data that has been collected. Therefore, it enables us to understand everything that we need to understand in order to put the data into perspective. In order to understand, the data set in this problem through descriptive statistics, we will use a frequency distribution. Frequency distribution groups the data into its respective categories and records the number of observations in each category enabling us to have a glance at it in a convenient manner (Jaggia & Kelly, 2014). It shows which category has high or lower observations as well as their concentration. Therefore, since we will be using ordinal data, frequency distribution will allow us to categorize and rank it. This will enable us to determine if recognizing the contributing factors to the problem will help solve the issue of declining sales at Nike.
Analyze which types of inferential statistics might be best for analysing the data, if you were to collect a sample.
Inferential statistics is important because it allows researchers to make reasonable judgments on the outcomes and conclude how the data can be collected after the study. However, based on the type of problem at Nike, we would like to extend the survey past the study period but due to various constraints, inferential statistics will enable us make plausible conclusions in regard to the problem (IrwinKalzema, 2014). Consequently, it will enable us estimate which factor contributes to the problem more than the other so as to extend it past the collection level. In trying to understand the problem at Nike, we will use regression analysis type of inferential statistics. This type of analysis is suitable in examining the relationship between two or more variables. Decline in sales is a dependent variable and the stiff competition, poor marketing strategies and changes in customer tastes and preferences are independent variables. Therefore, regression analysis will play a significant role in understanding the relationship between these variables. Regression analysis allows us to understand the dependent variable (decline in sales) changes with variance in the independent variables (stiff competition, poor marketing strategies and changes in customer tastes and preferences).
From the data, we would like to predict or forecast the future trends of the problem hence the reason why we chose to use regression analysis. Secondly, we would like to determine which among the independent variables has a relationship with the dependent variable allowing us to explore the relation

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