Determine if each curve (in orange) is a valid probability density function (i.e. if the total area under the function = 1)
Table of contents
- 1. Introduction to Statistics53m
- 2. Describing Data with Tables and Graphs2h 1m
- 3. Describing Data Numerically2h 8m
- 4. Probability2h 26m
- 5. Binomial Distribution & Discrete Random Variables3h 28m
- 6. Normal Distribution & Continuous Random Variables2h 21m
- 7. Sampling Distributions & Confidence Intervals: Mean3h 37m
- Sampling Distribution of the Sample Mean and Central Limit Theorem19m
- Distribution of Sample Mean - Excel23m
- Introduction to Confidence Intervals22m
- Confidence Intervals for Population Mean1h 26m
- 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 20m
- 9. Hypothesis Testing for One Sample5h 13m
- Steps in Hypothesis Testing1h 13m
- Performing Hypothesis Tests: Means1h 1m
- Hypothesis Testing: Means - Excel42m
- Performing Hypothesis Tests: Proportions39m
- Hypothesis Testing: Proportions - Excel27m
- Performing Hypothesis Tests: Variance12m
- Critical Values and Rejection Regions29m
- Link Between Confidence Intervals and Hypothesis Testing12m
- Type I & Type II Errors15m
- 10. Hypothesis Testing for Two Samples5h 35m
- Two Proportions1h 12m
- Two Proportions Hypothesis Test - Excel28m
- Two Means - Unknown, Unequal Variance1h 2m
- 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
- Two Variances and F Distribution29m
- Two Variances - Graphing Calculator15m
- 11. Correlation1h 24m
- 12. Regression1h 59m
- 13. Chi-Square Tests & Goodness of Fit2h 31m
- 14. ANOVA2h 1m
6. Normal Distribution & Continuous Random Variables
Uniform Distribution
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Join thousands of students who trust us to help them ace their exams!Watch the first videoMultiple Choice
Determine if each curve (in orange) is a valid probability density function (i.e. if the total area under the function = 1)

A
Yes, because the area under the curve equals 1
B
No, because the area under the curve =
C
No, because the curve does not touch the x-axis
D
Yes, because the area under the curve is slightly more than 1.
Verified step by step guidance1
Step 1: Understand the definition of a probability density function (PDF). A valid PDF must satisfy two conditions: (1) The function must be non-negative for all values of x, and (2) The total area under the curve must equal 1.
Step 2: Analyze the graph provided. The orange curve is a horizontal line at y = 0.2 between x = 1 and x = 5. Outside this interval, the curve touches the x-axis, meaning the function is zero.
Step 3: Calculate the area under the curve. Since the curve is constant at y = 0.2 over the interval [1, 5], the area can be calculated using the formula for the area of a rectangle: Area = height × width. Here, height = 0.2 and width = 5 - 1 = 4.
Step 4: Verify if the total area equals 1. Substitute the values into the formula: Area = 0.2 × 4. Check if this result equals 1 to determine if the curve is a valid PDF.
Step 5: Conclude based on the calculation. If the area equals 1, the curve is a valid PDF. If the area does not equal 1, the curve is not a valid PDF.
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