When using the Student's distribution to construct a confidence interval for the population mean, which of the following conditions must be met?
Table of contents
- 1. Intro to Stats and Collecting Data1h 14m
- 2. Describing Data with Tables and Graphs1h 56m
- 3. Describing Data Numerically2h 0m
- 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
7. Sampling Distributions & Confidence Intervals: Mean
Confidence Intervals for Population Mean
Multiple Choice
When drawing independent random samples from two normal populations, what is the distribution of the difference between the sample means ?
A
It follows a chi-square distribution.
B
It is normally distributed.
C
It follows a uniform distribution.
D
It is always skewed to the right.
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Verified step by step guidance1
Identify the populations and samples: We have two independent random samples drawn from two normal populations. Let the sample means be \( \overline{x}_1 \) and \( \overline{x}_2 \).
Recall the distribution of sample means: Since each population is normal, each sample mean \( \overline{x}_1 \) and \( \overline{x}_2 \) is also normally distributed due to the properties of the normal distribution.
Consider the difference of the sample means: The difference \( \mu = \overline{x}_1 - \overline{x}_2 \) is a linear combination of two independent normal random variables.
Use the property of normal distributions: The difference of two independent normal random variables is also normally distributed. Therefore, \( \mu \) follows a normal distribution.
Summarize the result: The distribution of \( \overline{x}_1 - \overline{x}_2 \) is normal, with mean equal to the difference of the population means and variance equal to the sum of the variances of the sample means.
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