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Table of contents
- 1. Introduction to Statistics53m
- 2. Describing Data with Tables and Graphs2h 2m
- 3. Describing Data Numerically2h 8m
- 4. Probability2h 26m
- 5. Binomial Distribution & Discrete Random Variables3h 28m
- 6. Normal Distribution & Continuous Random Variables2h 21m
- 7. Sampling Distributions & Confidence Intervals: Mean3h 37m
- Sampling Distribution of the Sample Mean and Central Limit Theorem19m
- Distribution of Sample Mean - ExcelBonus23m
- Introduction to Confidence Intervals22m
- Confidence Intervals for Population Mean1h 26m
- 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 20m
- 9. Hypothesis Testing for One Sample5h 15m
- Steps in Hypothesis Testing1h 13m
- Performing Hypothesis Tests: Means1h 1m
- Hypothesis Testing: Means - ExcelBonus42m
- Performing Hypothesis Tests: Proportions39m
- Hypothesis Testing: Proportions - ExcelBonus27m
- Performing Hypothesis Tests: Variance12m
- Critical Values and Rejection Regions29m
- Link Between Confidence Intervals and Hypothesis Testing12m
- Type I & Type II Errors16m
- 10. Hypothesis Testing for Two Samples5h 35m
- Two Proportions1h 12m
- Two Proportions Hypothesis Test - ExcelBonus28m
- Two Means - Unknown, Unequal Variance1h 2m
- 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 CalculatorBonus15m
- 11. Correlation1h 24m
- 12. Regression3h 42m
- 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 Slope32m
- Enabling Data Analysis ToolpakBonus1m
- Regression Readout of the Data Analysis Toolpak - ExcelBonus21m
- Prediction Intervals13m
- Prediction Intervals - ExcelBonus19m
- Multiple Regression - ExcelBonus29m
- Quadratic Regression23m
- Quadratic Regression - ExcelBonus10m
- 13. Chi-Square Tests & Goodness of Fit2h 31m
- 14. ANOVA2h 32m
7. Sampling Distributions & Confidence Intervals: Mean
Confidence Intervals for Population Mean
Multiple Choice
Find each probability.
(B)
A
0.91
B
0.83
C
0.083
D
0.086
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Verified step by step guidance1
Step 1: Recognize that the problem involves finding the probability for a t-distribution. The given inequality is P(-1.5 < T < 1.5), and the degrees of freedom (df) are 8.
Step 2: Understand that for a t-distribution, probabilities are calculated using the cumulative distribution function (CDF). The probability P(-1.5 < T < 1.5) can be expressed as the difference between two cumulative probabilities: P(T < 1.5) - P(T < -1.5).
Step 3: Use a t-distribution table or statistical software to find the cumulative probabilities for T = 1.5 and T = -1.5 with df = 8. For example, look up the CDF value for t = 1.5 and t = -1.5 in the table or use a function like T.DIST in Excel or a similar function in statistical software.
Step 4: Subtract the cumulative probability for T = -1.5 from the cumulative probability for T = 1.5 to find the probability P(-1.5 < T < 1.5). This step ensures that you are calculating the area under the t-distribution curve between -1.5 and 1.5.
Step 5: Verify your result by checking that the calculated probability is reasonable (e.g., it should be between 0 and 1) and matches the expected range for the given degrees of freedom.
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