Statistical methods are most effective for analyzing which type of data?
Table of contents
- 1. Intro to Stats and Collecting Data1h 14m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically2h 5m
- 4. Probability2h 16m
- 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 - Excel23m
- Introduction to Confidence Intervals15m
- Confidence Intervals for Population Mean1h 18m
- Determining the Minimum Sample Size Required12m
- Finding Probabilities and T Critical Values - Excel28m
- Confidence Intervals for Population Means - Excel25m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 25m
- 9. Hypothesis Testing for One Sample3h 29m
- 10. Hypothesis Testing for Two Samples4h 50m
- Two Proportions1h 13m
- Two Proportions Hypothesis Test - Excel28m
- Two Means - Unknown, Unequal Variance1h 3m
- Two Means - Unknown Variances Hypothesis Test - Excel12m
- Two Means - Unknown, Equal Variance15m
- Two Means - Unknown, Equal Variances Hypothesis Test - Excel9m
- Two Means - Known Variance12m
- Two Means - Sigma Known Hypothesis Test - Excel21m
- Two Means - Matched Pairs (Dependent Samples)42m
- Matched Pairs Hypothesis Test - Excel12m
- 11. Correlation1h 24m
- 12. Regression1h 50m
- 13. Chi-Square Tests & Goodness of Fit2h 21m
- 14. ANOVA1h 57m
4. Probability
Basic Concepts of Probability
Struggling with Statistics?
Join thousands of students who trust us to help them ace their exams!Watch the first videoMultiple Choice
Which of the following is not a property of the t distribution?
A
The variance of the t distribution is always equal to for all degrees of freedom.
B
The t distribution is symmetric about .
C
The t distribution has heavier tails than the normal distribution.
D
As the degrees of freedom increase, the t distribution approaches the standard normal distribution.
Verified step by step guidance1
Step 1: Understand the t distribution and its key properties. The t distribution is a probability distribution used in statistics, especially when dealing with small sample sizes and unknown population standard deviations.
Step 2: Recall that the t distribution is symmetric about zero, meaning its shape is mirrored on both sides of the mean (which is zero). This is a fundamental property.
Step 3: Recognize that the t distribution has heavier tails than the normal distribution. This means it gives more probability to values far from the mean, which accounts for extra uncertainty with small samples.
Step 4: Know that as the degrees of freedom (df) increase, the t distribution approaches the standard normal distribution. This is because with more data, the estimate of the population standard deviation becomes more accurate.
Step 5: Understand the variance of the t distribution depends on the degrees of freedom and is not always equal to 1. Specifically, the variance is given by \(\frac{\nu}{\nu - 2}\) for degrees of freedom \(\nu > 2\), which means it changes with \(\nu\) and is only equal to 1 in the limit as \(\nu\) approaches infinity.
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