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WorksheetsQ2 UNIT TEST - STATSTECH12
Total questions: 15
Worksheet time: 9mins
Teacher Volther wants to compare the test scores of students before and after a new teaching method is introduced. The same group of students takes the test both before and after the method is implemented.
Which statistical test should the teacher use to determine if there is a significant difference in the scores?
One-sample t-test
Paired-sample t-test
Independent-samples t-test
Chi-square test
Sir Les is comparing the average anxiety levels between two different treatment groups (Group A and Group B). Each group is independently selected, and the anxiety levels are measured using a standardized scale.
Which type of t-test would be appropriate for this comparison?
Paired-sample t-test
Independent-samples t-test
One-sample t-test
T-test
Jhazz wants to determine if the average weight of people in a community is different from the national average weight. The researcher collects a sample of 50 people from the community and compares their average weight to the national average.
Which statistical test should the researcher use?
Paired-sample t-test
Independent-samples t-test
One-sample t-test
Two-way ANOVA
Dr. Sangil wants to compare the weight loss of two different groups: one that followed a high-protein diet and the other a low-carb diet. The participants in the two groups are different (independent groups).
Which t-test is appropriate for comparing the weight loss between the two groups?
Paired-sample t-test
Independent-samples t-test
One-sample t-test
Multiple regression analysis
You want to test if a new mobile app has an effect on users' sleep quality. You measure sleep quality before and after using the app for one month, using the same participants.
Which statistical test should you use to determine if there is a significant change in sleep quality?
Paired-sample t-test
Independent-samples t-test
One-sample t-test
Chi-square test
It is a statistical test used to determine whether there is a significant difference between the means of two groups or between a sample and a known population mean. It helps to assess if the differences observed in the data are likely due to random chance or if they reflect a true underlying difference.
(a)
This test compares the mean of a single sample to a known population mean. It's used when you want to test if the sample mean is significantly different from a specific value (like a national average).
(a)
This test compares the means of two independent groups to determine if there is a statistically significant difference between them. The groups should be unrelated (e.g., two different sets of people).
(a)
This test compares the means of two related groups. It's used when the data points are paired or matched in some way, such as measuring the same individuals before and after an intervention.
(a)
This value helps to determine the significance of the test. If the value is smaller than a chosen significance level (e.g., 0.05), the null hypothesis is rejected, indicating a significant difference.
(a)
What is the main purpose of a t-test?
To compare proportions between two groups
To assess the significance of the correlation between two variables
To determine if there is a significant difference between the means of two groups or a sample and a population
To analyze the variance within a single group
Which of the following is true about a one-sample t-test?
It compares the means of two independent groups.
It compares the mean of a sample to a known population mean.
It is used when comparing paired data from the same subjects.
It compares proportions between two groups.
Which assumption is made when performing an independent-samples t-test?
The two groups being compared have the same number of participants.
The variances of the two groups being compared are equal (homogeneity of variance).
The two groups must be related or dependent.
All of the above
What does a p-value less than 0.05 typically indicate in a t-test?
The null hypothesis is accepted, and the result is not significant.
The null hypothesis is rejected, and the result is statistically significant.
The test is invalid, and the results cannot be interpreted.
The difference between the groups is likely due to sampling error.
Which of the following is a correct assumption of a t-test when the sample size is small?
The data must be normally distributed.
The sample must be randomly selected, but normality is not necessary.
The sample should be a perfect representation of the population.
There must be no outliers in the data.
