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Q1: Define the following terms:

a. correlation coefficient

b. scatter plot

c. bivariate relationship

Q2: Provide an example where the outlier is more important to the research than the other observations?

Q3: Identify when to use Spearman’s rho

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Answer 1

a) Correlation coefficient r measure of intensity or degree of linear relationship between two variables. It lies between -1 to +1

-1 means strong negative correlation.

+ 1 means strong positive correlation

b) Scatterplot is simplest way of the diagrammatic representation of bivariate data. Thus for the bivariate distribution (xi,yi) i=1,2,...,n if the values of the variable X and Y are plotted along the x axis and y axis respectively in the x-y plane the diagram of dots so obtained are called scatterplot.

c) bivariate relationship: Bivariate means two variable. Relationship between two variables x and y is known as bivariate relationship.

2) In regression analysis outlier is very important. Outlier is extreme data points or observations.

3) Whenever there is skewness in data or outliers in data in such case we can not use pearson correlation so we switch to spearman's rho. Spearman's rho is coefficient of correlation between the ranks of two variable.