Question no. 01
Should average disposable income be used to predict sales based on the sample of 14 sunflowers stores?

Answer to the question no. 01
➢ Average disposanble income should be used to predict sales. ➢ John Meynard Keynes, “The higher the income the higher the consumption is”. ➢ Consumption has a positive relation with disposable income. ➢ From the scatter diagram made by the given data, it is noted that as the disposable income increases the annual sales also increases.

[pic]

➢ Again, We know that the coefficient correlation is,
r = [pic][pic]

Here,
r = [pic]
= [pic]
= 0.70
Therefore, there is a strong positive correlation between the disposable income and the annual sales.

➢ The regression coefficient is 0.193. That means sales will increase by $0.193 if disposable income increase by $1.00.

“Based on these points we can conclude that, the average disposable income should be used to predict sales based on the sample of 14 sunflowers stores.”

Question no. 02
Should the management of Sunflowers accept the claims of Triangle’s leasing agents? Why or why not?

Answer to the question no. 02
The management should accept the claims of Triangle leasing agents.
The reasons are:
➢ There is a strong positive correlation between disposable income and sales, so it is easily predictable that there is a direct relationship between these two variables. ➢ Value of the coefficient of correlation is 0.70 and it is near to 1.00. That is if one variable, the disposal income increases, another variable, the annual sales will also increase. ➢ The regression coefficient is 0.193. Which means that, if the average disposable income increases by $1, annual sales will increase by $0.193.

Question no. 03
Is it possible that the average disposable income of the surrounding area is not an important factor in leasing new locations?...

...CorrelationCorrelation Co-efficient Definition:
A measure of the strength of linear association between two variables. Correlation will always between -1.0 and +1.0. If the correlation is positive, we have a positive relationship. If it is negative, the relationship is negative.
CorrelationCorrelation can be easily understood as co relation. To define. correlation is the average relationship between two or more variables. When the change in one variable makes or causes a change in other variable then there is a correlation between these two variables.
These correlated variables can move in the same direction or they can move in opposite direction. Not always there is a cause and effect relationship between the variables when there is a change; that might be due to uncertain change.
Simple Correlation is a correlation between two variables only; meaning the relationship between two variables. Event correlation and simple event correlation are the types of correlations mainly used in the industry point of view.
Types of Correlation
In Research Methodology of the Management, Correlation is broadly classified into six types as follows :
(1) Positive Correlation
(2) Negative Correlation
(3) Perfectly Positive...

... The principles and methods associated with this case study also apply to any number of variables other than strength and job performance.
Case Study Objectives
The purpose of this case study is to describe the logic behind the statistical principles and procedures listed below within the context of an applied problem. After a thorough exploration of this case study and all associated links you should be familiar with the principles and be able to apply them to similar situations. In addition, you should be able to use one of several popular statistical packages to carry out the analyses described in this case study.
The specific statistical principles associated with this study are:
* scatterplots
* covariance
* correlation
* linear regression
* multiple regression
Recommended Use
The principles presented in this case study have a number of issues associated with them. Therefore, we recommend that you take the time to explore the various links presented in this case study. Some of those links will take you to additional information regarding a particular statistical procedure or issue. Others will take you to simulations which demonstrate the principles or techniques being presented. These simulations give you hands-on experience with the various statistical procedures and principles.
Study Method and Procedure
Study Participants
The data presented in this case study were collected from 147 individuals working in...

...The purpose of this paper is to provide a response to a scenario by running a correlation and regression analysis for a statistics class assignment. The assignment provides a scenario with two part, pursuing ways to develop and maintain online and blended programs (Szapkiw, 2014, p. 2). This assignment required the use of SPSS to “choose the appropriate tests . . . run the tests and analyze the data” (Szapkiw, 2014, p. 14).
Structure
This assignment has two aspects and seven sections for the purpose of an assignment for a statistics class.
Research Question 1
Is there a statistically significant relationship between students’ total community score as measured by the Classroom Community Scale (Rovai, 2002) and the total perceived learning scores as measured by the Perceived CAP Learning Scale (Rovai et al., 2009) after controlling for gender among students enrolled in the Introduction to Statistics course?
Null Hypothesis 1
There is no significant relationship between students’ total community score as measured by the Classroom Community Scale (Rovai, 2002) and the total perceived learning scores as measured by the Perceived CAP Learning Scale (Rovai et al., 2009) after controlling for gender among students enrolled in the Introduction to Statistics course.
Alternative Hypothesis 1
There is a significant relationship between students’ total community score as measured by the Classroom Community Scale (Rovai, 2002) and the total perceived learning...

...Income Inequality Paper
The distribution of income in the United States has been growing more and more unequal since the 1980s, although there has been a slight decrease in the this distribution in the past decade. When focusing in on the 2nd and 4th quintile, it can be observed that the earnings gap increased between 1980 and 1990, but has continued to shrink since. Our text tells us that the three major market factors leading to income inequality are changes in supply ( the supply of less-educated workers rising faster than supply of college graduates), changes in demand ( the demand for more-educated workers increasing relative to the demand for less-educated workers), and institutional forces, such as the minimum wage and the decline of unions (Ehrenberg, 2012).
The main cause driving this unequal distribution of earnings is the rising demand for workers with high amounts of human capital (such as more experience and higher education) and the falling demand for workers with less human capital (individuals with less experience and less education). In other words, the returns of receiving an education have increased, and the more educated individuals are experiencing faster wage increases and faster career growth than individuals without these amounts of higher human capital (Gottschalk, 1997). The rising returns to education are related to “skill-biased technological change”, which is technological change that increases the...

...
CORRELATION
Md. Musa Khan
Lecturer
DBA, IIUC
musa_stat@yahoo.com
Definition:
If two or more variables vary in such a way that change in one are accompanied by changes in the other, these variables are said to be correlated. For example, here exists some relationship between family income and expenditure on luxury items, price of a commodity and amount demanded, increase in rainfall up to a point and production of a rice, etc. The statistical tool with the help of which these relationships between two or more than two variables is studied is called correlation. Therefore the relationship between two or more variables is called correlation.
Co-efficient of correlation:
The measure of correlation is called the coefficient of correlation summarizes in one figure the direction and degree of correlation. It is denoted by r.
Types of correlation:
There are four types of correlations. They are
i. Simple correlation
ii. Multiple...

...Correlation
Chapter 10
Covariance and Correlation
What does it mean to say that two variables are associated with one another?
How can we mathematically formalize the concept of association?
Differences between Data Handling in Correlation & Experiment
1. Summarize entire relationship
• We don’t compute a mean Y (e.g., aggressive behavior) score at each X (e.g., violent tv watching). We summarize the entire relationship formed by all pairs of X-Y scores. This is the major advantage of correlation.
2. N = number of pairs
• Because we look at all X-Y pairs at once, we have ONE sample, with N representing the number of pairs
3. Variable X and Variable Y are arbitrary
• Either variable can be X or Y. It’s arbitrary. There is no IV or DV.
4. Scatterplot
• Data are graphed as a scatterplot of pairs of scores.
--HW Q--
The statistic that we calculate to determine the relationship between our variables is the Correlation Coefficient
This number tells us two things about the relationship:
Type of relationship
Strength of relationship
Types of Relationships
Linear: as scores on one variable increase, scores on the other variable either increase or decrease
Nonlinear: relationship between X and Y changes direction at some point
U: Age & difficulty moving
Inverted U: Alcohol consumed & feeling well
Correlational research focuses almost entirely on linear...

...Ariella Dayan (326883881)
Quantitative Research Methods- Shani Greenspan
November 25, 2012
The Correlation of Income Level and Happiness Level
This study will investigate the relationship between income and happiness. A very popular question in today’s society is whether money can buy happiness. Happiness has been shown to be related to many things. It is found to be related to social class, success, power, health, valued belongings, religious beliefs, companionship, being employed in a secure job, having a full social life, and more or less accumulation of money.
Research shows that money does not buy happiness but it comes indirectly from the higher rank in society that money brings. “The rank-income hypothesis” was tested and found that the ranked position of an individual’s income predicts general life satisfaction. Once someone has a large amount of money they may become part of a different social group which brings more confidence and satisfaction. A persons’ satisfaction and self-esteem will increase if his social rank increases or if those who once had the same social rank him decreases. People naturally feel better and more satisfied if they are better than others. (Boyce, C. et al. 2010)
People dedicate so much energy in trying to make more money, when having more money does not make them that much happier. People may be happy with their current level of wealth and stop trying to...

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