{"id":2023,"date":"2023-11-26T16:05:52","date_gmt":"2023-11-26T16:05:52","guid":{"rendered":"https:\/\/myknowledgehub.org\/?p=2023"},"modified":"2023-11-26T16:50:39","modified_gmt":"2023-11-26T16:50:39","slug":"research-methodology-chapter-12-1","status":"publish","type":"post","link":"https:\/\/myknowledgehub.org\/index.php\/2023\/11\/26\/research-methodology-chapter-12-1\/","title":{"rendered":"Research Methodology Chapter 12.1"},"content":{"rendered":"\t\t
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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"arrow,\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Correlation<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Correlation and Regression are the two analyses based on multivariate distribution. A multivariate distribution is described as a distribution of multiple variables.\u00a0<\/span><\/p>

\u00a0<\/span><\/i><\/b><\/p>

Correlation<\/span><\/i><\/b> is described as the analysis which lets us know the association or the absence of the relationship between two variables \u2018x<\/b>\u2019 and \u2018y<\/b>\u2019.\u00a0<\/span><\/p>

On the other end, Regression analysis<\/i><\/b>, predicts the value of the dependent variable based on the known value of the independent variable<\/i>, assuming that average mathematical relationship between two or more variables<\/i>.<\/span><\/p>

\u00a0<\/span><\/p>

The difference between correlation and regression is one of the commonly asked questions. Moreover, many people suffer ambiguity in understanding these two.\u00a0<\/span><\/p>

\u00a0<\/span><\/p>

The following table summarizes the differences between correlation and regression<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Basis for Comparison<\/span><\/b><\/p><\/td>

Correlation<\/span><\/b><\/p><\/td>

Regression<\/span><\/b><\/p><\/td><\/tr>

Meaning\u00a0<\/span><\/p><\/td>

Correlation is a statistical measure which determines co-relationship<\/i><\/b> or association of two variables<\/i><\/b>.\u00a0<\/span><\/p><\/td>

Regression describes how an independent variable is numerically related to the dependent variable<\/i><\/b>.<\/span><\/p><\/td><\/tr>

Usage\u00a0<\/span><\/p><\/td>

To represent linear relationship between two variables<\/i><\/b>.\u00a0<\/span><\/p><\/td>

To fit a best line and estimate one variable on the basis of another variable<\/i><\/b>.<\/span><\/p><\/td><\/tr>

Dependent and Independent variables\u00a0<\/span><\/p><\/td>

No difference\u00a0<\/span><\/p><\/td>

Both variables are different.<\/span><\/p><\/td><\/tr>

Indicates\u00a0<\/span><\/p><\/td>

Correlation coefficient indicates the extent to which two variables move together<\/span><\/i><\/b>.\u00a0<\/span><\/p><\/td>

Regression indicates the impact of a unit change in the known variable (x) on the estimated variable (y)<\/span><\/i><\/b>.<\/span><\/p><\/td><\/tr>

Objective\u00a0<\/span><\/p><\/td>

To find a numerical value expressing the relationship between variables.\u00a0<\/span><\/p><\/td>

To estimate values of random variable on the basis of the values of fixed variable.<\/span><\/p><\/td><\/tr><\/tbody><\/table>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Correlation is a statistical measure that quantifies the relationship between two variables. It helps us understand how changes in one variable are associated with changes in another variable. In this section, we will explore the concepts of correlation and its applications in various fields.<\/span><\/p>

Correlation is a statistical technique used to determine the strength and direction of the relationship between two variables<\/i><\/b>. It measures the degree to which the variables move together. The correlation coefficient, denoted by “r,” ranges from -1 to +1.\u00a0<\/span><\/p>

A <\/span>positive correlation <\/b><\/span>indicates a direct relationship, where an increase in one variable is associated with an increase in the other variable.\u00a0<\/span>Conversely, a <\/span>negative correlation <\/b><\/span>indicates an inverse relationship, where an increase in one variable is associated with a decrease in the other variable.<\/span><\/p>

\u00a0<\/span><\/p>

Positive Correlation:<\/span><\/b><\/p>

\u00a0<\/p>