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.

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.

3/4 ÷ 3/4

step-by-step explanation:

basically divide any proper fraction with itself to fit the criteria.

so if we are using 3/4, then:

3/4 ÷ 3/4 = 1

so 1 is the quotient.

and the numerators for both these fractions is 3.   and if we divide the numerators:

3 ÷ 3 = 1

we see that quotient is equal to our original quotient as well.

you already gave the answer

step-by-step explanation: