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 6.R.9
Textbook Question
In Exercises 8 and 9, assume that women have standing eye heights that are normally distributed with a mean of 59.7 in. and a standard deviation of 2.5 in. (based on anthropometric survey data from Gordon, Churchill, et al.).
Significance Instead of using 0.05 for identifying significant values, use the criteria that a value x is significantly high if P(x or greater) ≤ 0.01 and a value is significantly low if P(x or less) ≤ 0.01. Find the standing eye heights of women that separate significant values from those that are not significant. Using these criteria, is a woman’s standing eye height of 67 in. significantly high?

1
Step 1: Understand the problem. We are tasked with finding the standing eye heights that separate significant values from those that are not significant, based on the given criteria. Specifically, a value is significantly high if P(x or greater) ≤ 0.01, and significantly low if P(x or less) ≤ 0.01. Additionally, we need to determine if a standing eye height of 67 inches is significantly high.
Step 2: Recall the properties of the normal distribution. The problem states that the standing eye heights are normally distributed with a mean (μ) of 59.7 inches and a standard deviation (σ) of 2.5 inches. To find the critical values, we will use the z-score formula: z = (x - μ) / σ.
Step 3: Find the z-scores corresponding to the cumulative probabilities of 0.01 and 0.99. For the significantly low threshold, we need the z-score where P(x or less) = 0.01. For the significantly high threshold, we need the z-score where P(x or greater) = 0.01, which corresponds to P(x or less) = 0.99 (since the total area under the curve is 1). Use a z-table or statistical software to find these z-scores.
Step 4: Convert the z-scores back to x-values (standing eye heights) using the formula x = μ + zσ. Substitute the mean (μ = 59.7) and standard deviation (σ = 2.5) into the formula along with the z-scores obtained in Step 3 to calculate the critical standing eye heights.
Step 5: Determine if a standing eye height of 67 inches is significantly high. Calculate the z-score for x = 67 using the formula z = (x - μ) / σ. Compare this z-score to the critical z-score for significantly high values (from Step 3). If the z-score for 67 inches is greater than or equal to the critical z-score, then 67 inches is significantly high.

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Normal Distribution
Normal distribution is a probability distribution that is symmetric about the mean, indicating that data near the mean are more frequent in occurrence than data far from the mean. It is characterized by its bell-shaped curve, defined by its mean and standard deviation. In this context, the standing eye heights of women are assumed to follow a normal distribution, which allows for the application of statistical methods to determine significance.
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Z-Score
A Z-score measures how many standard deviations an element is from the mean. It is calculated by subtracting the mean from the value and then dividing by the standard deviation. In this question, calculating the Z-score for a standing eye height of 67 inches will help determine whether it falls within the significant range defined by the criteria of P(x or greater) ≤ 0.01.
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Significance Level
The significance level, often denoted as alpha (α), is the threshold used to determine whether a result is statistically significant. In this case, the criteria specify that a value is significantly high if the probability of observing that value or greater is less than or equal to 0.01. This means that only the most extreme values in the distribution will be considered significantly high, allowing for a more stringent test of significance.
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