Which of the following best illustrates the definition of a probability distribution?
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: Proportion2h 10m
- 9. Hypothesis Testing for One Sample5h 6m
- Steps in Hypothesis Testing1h 6m
- Performing Hypothesis Tests: Means1h 4m
- Hypothesis Testing: Means - Excel42m
- Performing Hypothesis Tests: Proportions37m
- Hypothesis Testing: Proportions - Excel27m
- Performing Hypothesis Tests: Variance12m
- Critical Values and Rejection Regions28m
- Link Between Confidence Intervals and Hypothesis Testing12m
- Type I & Type II Errors15m
- 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. Regression3h 33m
- Linear Regression & Least Squares Method26m
- Residuals12m
- Coefficient of Determination12m
- Regression Line Equation and Coefficient of Determination - Excel8m
- Finding Residuals and Creating Residual Plots - Excel11m
- Inferences for Slope31m
- Enabling Data Analysis Toolpak1m
- Regression Readout of the Data Analysis Toolpak - Excel21m
- Prediction Intervals13m
- Prediction Intervals - Excel19m
- Multiple Regression - Excel29m
- Quadratic Regression15m
- Quadratic Regression - Excel10m
- 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
Suppose Richard is taking a multiple-choice test with questions, each with answer choices, and he guesses randomly on each question. What is the probability that Richard will answer at least half of the questions correctly?
A
B
Less than
C
D
Verified step by step guidance1
Identify the type of probability distribution involved. Since Richard guesses randomly on each question with 4 choices, the number of correct answers follows a Binomial distribution with parameters \(n = 10\) (number of questions) and \(p = \frac{1}{4}\) (probability of guessing correctly).
Define the random variable \(X\) as the number of questions Richard answers correctly. We want to find \(P(X \geq 5)\), the probability that he answers at least half (5 or more) correctly.
Express the probability using the binomial probability formula:
\(P(X = k) = \binom{n}{k} p^k (1-p)^{n-k}\)
where \(\binom{n}{k}\) is the binomial coefficient representing the number of ways to choose \(k\) successes out of \(n\) trials.
Calculate the cumulative probability for \(k = 5\) to \(k = 10\):
\(P(X \geq 5) = \sum_{k=5}^{10} \binom{10}{k} \left(\frac{1}{4}\right)^k \left(\frac{3}{4}\right)^{10-k}\)
Sum these probabilities to find the total probability that Richard answers at least half the questions correctly. This sum will give the final probability, which you can then compare to the given options.
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