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Final project Answer the following question in three to five pages: 1.Using what you have researched and studied throughout Modules 1-7, write a report addressing a quantitative analysis (QA)...

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Final project

Answer the following question in three to five pages:

1.Using what you have researched and studied throughout Modules 1-7, write a report addressing a quantitative analysis (QA) project. Here, you are asked to select a business of interest and develop QA best practices that can be developed and implemented to increase revenues and/or decrease costs. Please provide at least three mathematical examples supporting your recommendations.


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Answered Same Day Apr 04, 2020

Solution

Viswanathan answered on Apr 06 2020
153 Votes
Discussion
The most common statistical techniques that are widely used in economic, business and financial sectors are qualitative and quantitative analysis and these two techniques are mainly used to differentiate the data and statistical analysis. The quantitative methods are commonly used to project the measurement of the objective variables that was collected using the collected information. This course progress helped me to understand use of quantitative analysis and thus allow for a deeper study that involves a higher number of participants and thus provides a great improvement in the generalization of the results. The quantitative methods are generally used to provide the describe the data by provided the summary statistics which normally provides support to generalizations about the phenomenon under study
The main drawback that I found in using the quantitative study is that it basically ignores the content of the study and thus provides a unavoidable biased nature. Also, this method involves larger sample into consideration and thus, consumes more man power, time and cost. Thus, it is better to have a discussion before selecting an appropriate method for analysis
Data Validation
The data validation should be performed before running the statistical analysis for the data collected. The data validation is the process of cleaning and validating the data and removing the outliers or extreme points in it. The outliers, if found has to be removed from the entire dataset and then, we need to perform the analysis. For categorical variables, we use frequency distribution to find the unusual points and for continuous variables summary statistics was used to determine the unusual observations. Missing values can either be replaced by the mode (for categorical data) or either by mean or median (for continuous data). Independent sample t test was used to determine the relationship between one continuous variable and one dichotomous variable, for example, testing the relationship between monthly income and gender (is male are getting higher income on an average when compared to that of females). Simple linear regression analysis and multiple linear regression analysis were used to predict the future values of the dependent variable. One of the most important steps to be performed before running the analysis is validating the data
Regression Analysis
Simple linear regression analysis was used to predict the future values of a dependent variable with one independent variable. On the other hand, multiple regression analysis was used...
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