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# OUANTITATIVE METHODS report group 5.pptx

I have no idea to my report kaya i need the power point of this

I have no idea to my report kaya i need the power point of this

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### OUANTITATIVE METHODS report group 5.pptx

1. 1. SECTION 5. Understanding One Variable and the Association of Two Variables
2. 2. › In many studies, we measure more than one variable for each individual. › For example, we measure precipitation and plant growth, or number of young with nesting habitat, or soil erosion and volume of water. We collect pairs of data and instead of examining each variable separately (univariate data), we want to find ways to describe bivariate data, › in which two variables are measured on each subject in our sample. Given such data, we begin by determining if there is a relationship between these two variables.
3. 3. › What are Correlation and Regression? › Correlation and regression are statistical measurements that are used to give a relationship between two variables. For example, suppose a person is driving an expensive car then it is assumed that she must be financially well. To numerically quantify this relationship, correlation and regression are used.
4. 4. CORRELATION AND REGRESSION › Correlation and regression are statistical techniques used to study the relationship between two or more variables. CORRELATION › Correlation is a measure of the strength and direction of the linear relationship between two variables. It ranges from -1 to 1, where -1 represents a perfect negative correlation (as one variable increases, the other decreases), 1 represents a perfect positive correlation (as one variable increases, so does the other), and 0 represents no correlation.
5. 5. CORRELATION DEFINATION Correlation can be defined as a measurement that is used to quantify the relationship between variables. If an increase (or decrease) in one variable causes a corresponding increase (or decrease) in another then the two variables are said to be directly correlated. Similarly, if an increase in one causes a decrease in another or vice versa, then the variables are said to be indirectly correlated. If a change in an independent variable does not cause a change in the dependent variable then they are uncorrelated. Thus, correlation can be positive (direct correlation), negative (indirect correlation), or zero. This relationship is given by the correlation coefficient.
6. 6. CORRELATION FORMULA › The formula for Pearson's correlation coefficient, a common measure of linear correlation between two variables, is given by: › Pearson's Correlation Coefficient: r= ∑n1(xi−¯¯¯x)(yi−¯¯¯y) √∑n1(xi−¯¯¯x)²∑n1(yi−¯¯¯y)² › where: › n is the number of data points › x and y are the two variables being correlated › ∑x and ∑y are the sums of the x and y values, respectively › ∑xy is the sum of the products of the x and y values › ∑x^2 and ∑y^2 are the sums of the squares of the x and y values, respectively. › The result, r, is a value between -1 and 1 that represents the strength and direction of the linear relationship between x and y.
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