An industrial psychologist is concerned that a recent round...

An industrial psychologist is concerned that a recent round of layoffs at a plant may have increased the stress felt by employees who retained their positions. To measure whether this survivor stress actually exists, the psychologist administered a stress measure to a sample of employees before and after the layoffs occurred. Evaluate whether self-reported stress increased from time $e_1$ to time $e_2$ by using a .01 significance level and a one-tailed test. $$ \begin{array}{lcc} \text { Employee } & \text { Stress Score }_1 & \text { Stress }_1 \text { Score }_2 \\ \hline \text { A } & 21 & 23 \\ \text { B } & 24 & 26 \\ \text { C } & 15 & 15 \\ \text { D } & 18 & 22 \\ \text { E } & 19 & 20 \\ \text { F } & 20 & 19 \\ \text { G } & 18 & 21 \\ \hline \end{array} $$

An industrial psychologist is concerned that a recent round of layoffs at a plant may have increased the stress felt by employees who retained their positions. To measure whether this survivor stress actually exists, the psychologist administered a stress measure to a sample of employees before and after the layoffs occurred. Evaluate whether self-reported stress increased from time $e_1$ to time $e_2$ by using a .01 significance level and a one-tailed test.
$$
\begin{array}{lcc}
\text { Employee } & \text { Stress Score }_1 & \text { Stress }_1 \text { Score }_2 \\
\hline \text { A } & 21 & 23 \\
\text { B } & 24 & 26 \\
\text { C } & 15 & 15 \\
\text { D } & 18 & 22 \\
\text { E } & 19 & 20 \\
\text { F } & 20 & 19 \\
\text { G } & 18 & 21 \\
\hline
\end{array}
$$

Key Concepts

One-Tailed Test

A one-tailed test is used when the research hypothesis predicts the direction of the effect (for example, an increase or a decrease). This type of test evaluates the probability of the relationship in only one direction, making it more powerful in detecting an effect in that specified direction compared to a two-tailed test.

Significance Level

The significance level is a threshold set by the researcher that determines how extreme the sample data must be, under the null hypothesis, before rejecting the null hypothesis. It is commonly set as .01, .05, or .10, indicating the probability of a Type I error, which is the incorrect rejection of a true null hypothesis.

Pretest-Posttest Design

A pretest-posttest design is an experimental setup where measurements are taken from the same subjects before and after an intervention or event. This design allows researchers to control for individual differences and directly assess the effect of an intervention or change, such as changes in stress levels over time.

Hypothesis Testing

Hypothesis testing is a statistical method used to decide whether there is enough evidence in a sample of data to infer that a certain condition is true for the entire population. It involves formulating a null hypothesis (usually stating that no effect or change exists) and an alternative hypothesis (stating the direction of the effect or change), and then using sample data to determine whether to reject the null hypothesis.

Paired Sample t-Test

A paired sample t-test is used when comparing two related samples, such as measurements taken from the same subjects at two different time points. This test determines whether there is a statistically significant difference between the means of these paired observations, accounting for the dependency between the paired measurements.

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