In statistics, why is a used more often than a when conducting studies?
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 represents a valid probability distribution?
A
A distribution where , , and
B
A distribution where ,
C
A distribution where ,
D
A distribution where , , and
Verified step by step guidance1
Recall the two main conditions for a valid probability distribution: (1) Each probability must be between 0 and 1 inclusive, i.e., \$0 \leq P(A) \leq 1\( for every event \)A\(, and (2) the sum of all probabilities must equal 1, i.e., \)\sum P(A_i) = 1\( where \)A_i$ are all possible events.
Check each given distribution to ensure all probabilities are within the range 0 to 1. If any probability is less than 0 or greater than 1, that distribution is invalid.
For each distribution, add up all the probabilities. Use the formula \(\sum P(A_i) = P(A) + P(B) + P(C) + \dots\) depending on the number of events given.
Verify if the sum of probabilities equals exactly 1. If the sum is less than or greater than 1, the distribution is not valid.
Identify the distribution that meets both criteria: all probabilities between 0 and 1, and the sum of probabilities equal to 1. This distribution represents a valid probability distribution.
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