The lengths of time it takes for new light bulbs to burn out are an example of 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 a required condition for a discrete probability function?
A
The sum of all possible probabilities is .
B
The sum of all possible probabilities is less than .
C
Probabilities can be greater than .
D
Each probability can be negative as long as the sum is .
Verified step by step guidance1
Understand that a discrete probability function assigns probabilities to each possible outcome of a discrete random variable.
Recall the two main conditions for a valid discrete probability function: (1) Each probability must be between 0 and 1 inclusive, and (2) the sum of the probabilities of all possible outcomes must equal 1.
Express the second condition mathematically as: \(\sum_{i} P(X = x_i) = 1\), where \(P(X = x_i)\) is the probability of the \(i\)-th outcome.
Recognize that probabilities cannot be negative or greater than 1 because they represent proportions of certainty.
Conclude that the required condition is that the sum of all possible probabilities is exactly 1, not less than or greater than 1.
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