A statistician wants to test for the equality of means in two independent samples drawn from normal populations. However, he will not perform the equal-variance t-test of the difference between the population means if the condition necessary for its use is not satisfied. The data are as follows: $$\begin{array} { | l | l | l | l | l | l | l | l | l | l | l | }
\hline \text { Sample 1: } & 7 & 9 & 6 & 15 & 7 & 10 & 8 & 12 & & \
\hline \text { Sample 2: } & 2 & 25 & 9 & 15 & 10 & 18 & 5 & 22 & 27 & 3 \
\hline
\end{array}$$ Given the data above, can the statistician conclude at the 5% significance level that the required condition is not satisfied?

Question

A statistician wants to test for the equality of means in two independent samples drawn from normal populations. However, he will not perform the equal-variance t-test of the difference between the population means if the condition necessary for its use is not satisfied. The data are as follows: $$\begin{array} { | l | l | l | l | l | l | l | l | l | l | l | } 
\hline \text { Sample 1: } & 7 & 9 & 6 & 15 & 7 & 10 & 8 & 12 & & \
\hline \text { Sample 2: } & 2 & 25 & 9 & 15 & 10 & 18 & 5 & 22 & 27 & 3 \
\hline
\end{array}$$ Given the data above, can the statistician conclude at the 5% significance level that the required condition is not satisfied?

Quizplus · Accepted Answer

The Answer of A statistician wants to test for the equality of means in two independent samples drawn from normal populations. However, he will not perform the equal-variance t-test of the difference between the population means if the condition necessary for its use is not satisfied. The data are as follows: $$\begin{array} { | l | l | l | l | l | l | l | l | l | l | l | } 
\hline \text { Sample 1: } & 7 & 9 & 6 & 15 & 7 & 10 & 8 & 12 & & \
\hline \text { Sample 2: } & 2 & 25 & 9 & 15 & 10 & 18 & 5 & 22 & 27 & 3 \
\hline
\end{array}$$ Given the data above, can the statistician conclude at the 5% significance level that the required condition is not satisfied?

A Statistician Wants to Test for the Equality of Means