In a two-group experiment where the treatment group (n = 50) has a mean score of 34.32 (SD = 10.45) and the control group (n = 50) has a mean score of 21.45 (SD = 9.22), a Cohen's d of 1.31 is considered an extremely strong effect size.

In a study evaluating a new psychological treatment, the treatment group ($M = 34.32$, $SD = 10.45$) is compared to a control group ($M = 21.45$, $SD = 9.22$), resulting in a Cohen's $d$ of $1.31$. Match each statistical component with its conceptual role in describing these results.

You are drafting the 'Results' section of a research paper. Your study found that the treatment group ($M = 34.32, SD = 10.45$) outperformed the control group ($M = 21.45, SD = 9.22$), resulting in a Cohen's $d$ of $1.31$. Which of the following is the most appropriate way to apply these descriptive statistics to your report?

A researcher is analyzing results where a treatment group ($M = 34.32, SD = 10.45$) and a control group ($M = 21.45, SD = 9.22$) produced a Cohen's $d$ of $1.31$. Arrange the following steps in the correct logical order required to move from initial data observation to a formal research conclusion.

In the provided example comparing a treatment group ($M = 34.32$) and a control group ($M = 21.45$), which type of analysis is explicitly identified as still being required for a formal research report?

A researcher finds that a treatment group ($n = 50, M = 34.32, SD = 10.45$) outperforms a control group ($n = 50, M = 21.45, SD = 9.22$) with an extremely strong Cohen's $d$ of $1.31$. Even when the magnitude of the difference is this visible, a student evaluating the evidence must judge these descriptive statistics as _____ for a formal scientific publication until inferential statistics (such as a $t$-test) are applied to rule out the possibility that the results occurred by chance.

In a research study comparing a treatment group ($M = 34.32$) to a control group ($M = 21.45$), the resulting Cohen's $d$ of $1.31$ is categorized as a(n) _____ statistic because it summarizes the magnitude of the observed effect but does not provide the probability that the results occurred by chance.

A student researcher writes a formal report comparing a treatment group ($n = 50, M = 34.32, SD = 10.45$) to a control group ($n = 50, M = 21.45, SD = 9.22$). Because the Cohen's $d$ of $1.31$ makes the treatment effect unmistakably obvious from the descriptive statistics alone, the student decides to omit the $t$-test from the report. This decision is appropriate for a formal research report.

In the study where the treatment group ($n = 50, M = 34.32, SD = 10.45$) is compared to the control group ($n = 50, M = 21.45, SD = 9.22$) and Cohen's $d = 1.31$, match each statistical element to the specific analytical role it plays in interpreting the results.

A peer reviewer is judging whether a two-group study report (treatment: $n = 50, M = 34.32, SD = 10.45$; control: $n = 50, M = 21.45, SD = 9.22$; Cohen's $d = 1.31$) is statistically complete and defensible. Arrange the following evaluative steps in the order a thorough reviewer should apply them.

Based on the provided research example, state the sample size, mean score, and standard deviation for both the treatment and control groups. Additionally, state the value of Cohen's $d$ and identify which class of statistics (like a $t$-test) is still required to complete a formal research report.

Evaluate the student researcher's conclusion. Explain whether descriptive statistics and effect sizes alone are sufficient for a formal research report in this scenario, and justify why or why not using the concepts presented in the text.

Suppose you are writing the Results section of a formal research report using the data from the study: treatment group ($n = 50, M = 34.32, SD = 10.45$), control group ($n = 50, M = 21.45, SD = 9.22$), and Cohen's $d = 1.31$. Apply the reporting requirements mentioned in the text to describe what additional analysis must be conducted and reported to complete your formal write-up.