Researcher Predicts That Watching A Film On Institutionaliza
Researcher Predicts That Watching A Film On Institutionalization Will
Researcher predicts that watching a film on institutionalization will change students’ attitudes about chronically mentally ill patients. The researcher randomly selects a class of 36 students, shows them the film, and gives them a questionnaire about their attitudes. The mean score on the questionnaire for these 36 students is 70. The score for people in general on this questionnaire is 75, with a standard deviation of 12. Using the five steps of hypothesis testing and the 5% significance level (i.e., alpha = .05), does showing the film change students’ attitudes towards the chronically mentally ill?
What does it mean to set alpha at .05? What is your null hypothesis? Alternate hypothesis? Is this a one-tailed or two-tailed hypothesis? What is the critical z? Calculate the obtained z. Do you reject or fail to reject the null hypothesis? State in words what you have found.
Paper For Above instruction
Introduction
The primary goal of this study is to determine whether viewing a film on institutionalization influences students’ attitudes toward chronically mentally ill patients. This inquiry employs hypothesis testing methodology to assess whether the observed difference in attitudes between students exposed to the film and the general population is statistically significant. By applying the principles of inferential statistics, particularly the z-test, the study aims to provide empirical evidence to support or refute the hypothesis that the film has a measurable impact on perceptions of mental illness.
Understanding Significance Level (Alpha)
Setting alpha at 0.05 signifies that the researcher has agreed to accept a 5% chance of erroneously rejecting the null hypothesis when it is actually true, known as a Type I error. This threshold defines the level of risk deemed acceptable for declaring a statistically significant effect. In practical terms, if the p-value obtained from the test is less than 0.05, the results are considered statistically significant, and the null hypothesis will be rejected. Conversely, if the p-value exceeds this threshold, the null hypothesis cannot be rejected, implying that any observed differences could plausibly be due to random variation.
Formulating Hypotheses
The null hypothesis (H₀) posits that there is no effect of watching the film on students’ attitudes; mathematically, it asserts that the mean attitude score of the students who watched the film is equal to the mean score of the general population:
H₀: μ = 75
The alternative hypothesis (H₁) suggests that the film influences attitudes, leading to a difference in the mean scores:
H₁: μ ≠ 75
Given that the hypothesis testing is examining for any difference—not specifically an increase or decrease—this is a two-tailed test.
Critical Z-Value
At a 5% significance level for a two-tailed test, the critical z-values are ±1.96. These values delineate the threshold beyond which the null hypothesis is rejected if the test statistic falls in either tail of the standard normal distribution.
Calculating the Z-Score
The z-score formula for a sample mean is:
\[
z = \frac{\bar{x} - \mu}{\sigma / \sqrt{n}}
\]
Where:
* \(\bar{x}\) = sample mean = 70
* \(\mu\) = population mean = 75
* \(\sigma\) = standard deviation = 12
* \(n\) = sample size = 36
Calculating the standard error:
\[
SE = \frac{12}{\sqrt{36}} = \frac{12}{6} = 2
\]
Calculating the z-value:
\[
z = \frac{70 - 75}{2} = \frac{-5}{2} = -2.5
\]
Decision and Interpretation
Since the calculated z-value of -2.5 exceeds the critical value of ±1.96 in magnitude, it falls into the rejection region of the distribution. Therefore, we reject the null hypothesis at the 0.05 significance level.
In words, this indicates that there is statistically significant evidence to suggest that watching the film has altered students’ attitudes toward chronically mentally ill patients. The data imply that the exposure to the film led to a measurable change, specifically, a decrease in attitude scores compared to the general population, which may reflect more negative or less favorable perceptions following the film.
Conclusion
Using hypothesis testing procedures, the study demonstrates that viewing a film on institutionalization significantly influences students' attitudes regarding the mentally ill. The rejection of the null hypothesis at the 5% significance level supports the assertion that media representations like films can impact perceptions and possibly reduce stigma associated with mental illness. Future research could explore the nature and direction of these attitude changes in more detail and assess long-term effects.
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