We want to explore the difference between salary (in dollars) and the number of years of job experience that an employee has. Which of the following is the most appropriate statistical test to use to determine if there is a relationship between salary and years of experience? Two-sample t-test Chi-squared test for independence Inference for regression ANOVA Matched pairs

Inference for Regression

Step-by-step explanation:

Let us try to understand the difference between each of them.

1) Two  sample t- test : the following assumptions must be used while applying the t- tests.

The samples of n observations X₁,X₂,X₃,X n is selected  randomly.The population from which the small sample is drawn is normal.This is essential for X` and s , the two components of the statistics t, to be independent. it has , however been shown that slight departures from normality do not seriously effect the tests.In case of two small samples both the samples are selected randomly , both the populations are normal and both the populations have equal variances.

2) Chi - squared Test for independence:

The two attributes A and B are said to be independent if the actual frequency equals the expected one , that is, if  (AB) = (A)(B)/ N

Similarly α and β will be independent is (αβ) = ( α)( β)/ N and so on.

3) Inference for Regression

When both X and Y are observed at random i.e the sample values are from a bi variate population there are two regression equations , each obtained by choosing that variable as dependent whose average value is to be estimated and treating the other variable as independent .

4) A N O V A

The  various sources of variation , degrees of freedom , the sum of squares and the mean squares associated  with the sources are generally shown in a table called analysis of variance table or A N O V A table.

5) Matched pairs

It can be used when the experiment has only two events or possibilities and each variable can be grouped in either of the two conditions. Example people having C O V I D 19 and not having C O V I D 19.

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Step-by-step explanation: