Table of contents
- 1. Intro to Stats and Collecting Data55m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically1h 45m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables2h 33m
- 6. Normal Distribution and Continuous Random Variables1h 38m
- 7. Sampling Distributions & Confidence Intervals: Mean1h 3m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 12m
- 9. Hypothesis Testing for One Sample1h 1m
- 10. Hypothesis Testing for Two Samples2h 8m
- 11. Correlation48m
- 12. Regression1h 4m
- 13. Chi-Square Tests & Goodness of Fit1h 20m
- 14. ANOVA1h 0m
6. Normal Distribution and Continuous Random Variables
Standard Normal Distribution
Problem 5.R.38
Textbook Question
In Exercises 37–42, use the Standard Normal Table or technology to find the z-score that corresponds to the cumulative area or percentile.
0.1

1
Identify the problem: You are tasked with finding the z-score that corresponds to a cumulative area (or percentile) of 0.1. This means that 10% of the data lies to the left of the z-score in a standard normal distribution.
Understand the relationship: The cumulative area represents the probability that a randomly selected value from the standard normal distribution is less than or equal to the z-score. The standard normal distribution has a mean of 0 and a standard deviation of 1.
Use the Standard Normal Table or technology: Locate the cumulative area of 0.1 in the Standard Normal Table. The table typically provides cumulative probabilities for z-scores. Alternatively, use statistical software or a calculator with an inverse normal function (e.g., invNorm in a TI calculator).
Interpret the result: The z-score corresponding to a cumulative area of 0.1 will be negative because the area is less than 0.5, indicating it is on the left side of the mean in the standard normal distribution.
Verify your result: Double-check the z-score by plugging it back into the cumulative probability formula or using technology to ensure the cumulative area is approximately 0.1.

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Z-Score
A z-score is a statistical measurement that describes a value's relationship to the mean of a group of values. It is calculated by subtracting the mean from the value and then dividing by the standard deviation. Z-scores indicate how many standard deviations an element is from the mean, allowing for comparison across different datasets.
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Standard Normal Distribution
The standard normal distribution is a special case of the normal distribution where the mean is 0 and the standard deviation is 1. It is represented by the bell-shaped curve and is used to determine probabilities and percentiles for normally distributed data. The area under the curve corresponds to probabilities, making it essential for finding z-scores.
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Cumulative Area
Cumulative area refers to the total area under the curve of a probability distribution up to a certain point. In the context of the standard normal distribution, it represents the probability that a randomly selected score will be less than or equal to a specific z-score. This concept is crucial for interpreting z-scores in terms of percentiles and probabilities.
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