Table of contents
- 1. Intro to Stats and Collecting Data1h 14m
- 2. Describing Data with Tables and Graphs1h 56m
- 3. Describing Data Numerically2h 5m
- 4. Probability2h 17m
- 5. Binomial Distribution & Discrete Random Variables3h 6m
- 6. Normal Distribution and Continuous Random Variables2h 11m
- 7. Sampling Distributions & Confidence Intervals: Mean3h 23m
- Sampling Distribution of the Sample Mean and Central Limit Theorem19m
- Distribution of Sample Mean - ExcelBonus23m
- Introduction to Confidence Intervals15m
- Confidence Intervals for Population Mean1h 18m
- Determining the Minimum Sample Size Required12m
- Finding Probabilities and T Critical Values - ExcelBonus28m
- Confidence Intervals for Population Means - ExcelBonus25m
- 8. Sampling Distributions & Confidence Intervals: Proportion2h 10m
- 9. Hypothesis Testing for One Sample5h 8m
- Steps in Hypothesis Testing1h 6m
- Performing Hypothesis Tests: Means1h 4m
- Hypothesis Testing: Means - ExcelBonus42m
- Performing Hypothesis Tests: Proportions37m
- Hypothesis Testing: Proportions - ExcelBonus27m
- Performing Hypothesis Tests: Variance12m
- Critical Values and Rejection Regions28m
- Link Between Confidence Intervals and Hypothesis Testing12m
- Type I & Type II Errors16m
- 10. Hypothesis Testing for Two Samples5h 37m
- Two Proportions1h 13m
- Two Proportions Hypothesis Test - ExcelBonus28m
- Two Means - Unknown, Unequal Variance1h 3m
- Two Means - Unknown Variances Hypothesis Test - ExcelBonus12m
- Two Means - Unknown, Equal Variance15m
- Two Means - Unknown, Equal Variances Hypothesis Test - ExcelBonus9m
- Two Means - Known Variance12m
- Two Means - Sigma Known Hypothesis Test - ExcelBonus21m
- Two Means - Matched Pairs (Dependent Samples)42m
- Matched Pairs Hypothesis Test - ExcelBonus12m
- Two Variances and F Distribution29m
- Two Variances - Graphing CalculatorBonus16m
- 11. Correlation1h 24m
- 12. Regression3h 33m
- Linear Regression & Least Squares Method26m
- Residuals12m
- Coefficient of Determination12m
- Regression Line Equation and Coefficient of Determination - ExcelBonus8m
- Finding Residuals and Creating Residual Plots - ExcelBonus11m
- Inferences for Slope31m
- Enabling Data Analysis ToolpakBonus1m
- Regression Readout of the Data Analysis Toolpak - ExcelBonus21m
- Prediction Intervals13m
- Prediction Intervals - ExcelBonus19m
- Multiple Regression - ExcelBonus29m
- Quadratic Regression15m
- Quadratic Regression - ExcelBonus10m
- 13. Chi-Square Tests & Goodness of Fit2h 21m
- 14. ANOVA2h 29m
9. Hypothesis Testing for One Sample
Performing Hypothesis Tests: Means
Multiple Choice
A university claims that the average SAT math score of its incoming freshmen is 600. A skeptical education researcher believes this might not be accurate. The researcher collects a random sample of 40 students and finds a sample mean SAT math score of 622. The population standard deviation is known to be 70. Using a significance level of = 0.05, test the researcher’s claim.
A
Since P-val > α, we fail to reject null hypothesis. There is NOT enough evidence that SAT math scores do NOT have an average of 600.
B
Since P-val < α, we fail to reject null hypothesis. There is NOT enough evidence that SAT math scores do NOT have an average of 600.
C
Since P-val > α, we reject null hypothesis. There is enough evidence that SAT math scores do NOT have an average of 600.
D
Since P-val < , we reject null hypothesis. There is enough evidence that SAT math scores do NOT have an average of 600.
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Verified step by step guidance1
Step 1: Define the null hypothesis (H₀) and the alternative hypothesis (H₁). The null hypothesis is H₀: μ = 600, which states that the average SAT math score is 600. The alternative hypothesis is H₁: μ ≠ 600, which states that the average SAT math score is not 600.
Step 2: Identify the test statistic formula for a z-test since the population standard deviation is known. The formula is: , where x̄ is the sample mean, μ is the population mean, σ is the population standard deviation, and n is the sample size.
Step 3: Substitute the given values into the formula. Here, x̄ = 622, μ = 600, σ = 70, and n = 40. Calculate the z-test statistic using the formula provided in Step 2.
Step 4: Determine the critical z-value for a two-tailed test at a significance level of α = 0.05. For α = 0.05, the critical z-values are approximately ±1.96. Compare the calculated z-test statistic to these critical values to decide whether to reject or fail to reject the null hypothesis.
Step 5: Calculate the p-value corresponding to the z-test statistic. If the p-value is less than α = 0.05, reject the null hypothesis. If the p-value is greater than α = 0.05, fail to reject the null hypothesis. Interpret the result in the context of the problem.
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Multiple Choice
In the context of performing hypothesis tests about means, the t-test is principally a test of which parameter?
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