What are the properties of the normal density curve?
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
6. Normal Distribution and Continuous Random Variables
Standard Normal Distribution
Problem 7.2.11c
Textbook Question
In Problems 5–12, find the indicated areas. For each problem, be sure to draw a standard normal curve and shade the area that is to be found.
Determine the total area under the standard normal curve
c. to the left of z = –0.24 or to the right of z = 1.20
Verified step by step guidance1
First, understand that the problem asks for the total area under the standard normal curve to the left of z = -0.24 or to the right of z = 1.20. This means we are looking for the combined probability of these two regions.
Draw a standard normal curve (a bell-shaped curve centered at 0) and mark the points z = -0.24 and z = 1.20 on the horizontal axis. Shade the area to the left of z = -0.24 and the area to the right of z = 1.20 to visualize the regions of interest.
Recall that the total area under the standard normal curve is 1. The area to the left of a z-value corresponds to the cumulative probability up to that z-value, which can be found using the standard normal distribution table or a calculator.
Find the cumulative area to the left of z = -0.24, denoted as \(P(Z < -0.24)\), and find the cumulative area to the left of z = 1.20, denoted as \(P(Z < 1.20)\). Then, calculate the area to the right of z = 1.20 by subtracting the cumulative area from 1: \(P(Z > 1.20) = 1 - P(Z < 1.20)\).
Finally, add the two areas together to get the total area: \(P(Z < -0.24) + P(Z > 1.20)\). This sum represents the probability of being either less than -0.24 or greater than 1.20 under the standard normal curve.
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Standard Normal Distribution
The standard normal distribution is a normal distribution with a mean of 0 and a standard deviation of 1. It is symmetric about zero, and its total area under the curve equals 1. Z-scores represent the number of standard deviations a value is from the mean.
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Z-Score and Area Under the Curve
A z-score indicates a position on the standard normal curve. The area to the left of a z-score corresponds to the cumulative probability up to that point. Finding areas to the left or right of z-values involves using standard normal tables or technology to determine probabilities.
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Addition Rule for Probabilities
When finding the total area for 'to the left of z = –0.24 or to the right of z = 1.20,' the addition rule applies. Since these two regions do not overlap, their probabilities can be added directly to find the combined area under the curve.
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