Forecast and Actual Temperatures Listed below are actual temperatures (°F) along with the temperatures that were forecast five days earlier (data collected by the author). Use a 0.05 significance level to test the claim that differences between actual temperatures and temperatures forecast five days earlier are from a population with a mean of 0°F.
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 57m
- 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
9. Hypothesis Testing for One Sample
Performing Hypothesis Tests: Means
Problem 8.1.21e
Textbook Question
Reading Rates The reading speed of second-grade students is approximately normal, with a mean of 90 words per minute (wpm) and a standard deviation of 10 wpm.
e. A teacher instituted a new reading program at school. After 10 weeks in the program, it was found that the mean reading speed of a random sample of 20 second-grade students was 92.8 wpm. What might you conclude based on this result?
Verified step by step guidance1
Identify the population parameters: the mean reading speed \( \mu = 90 \) wpm and the standard deviation \( \sigma = 10 \) wpm, with the reading speeds assumed to be normally distributed.
Recognize that the sample size \( n = 20 \) and the sample mean \( \bar{x} = 92.8 \) wpm are given after the new reading program.
Calculate the standard error of the mean (SEM) using the formula:
\[ \\text{SEM} = \\frac{\\sigma}{\\sqrt{n}} = \\frac{10}{\\sqrt{20}} \]
Compute the test statistic (z-score) to compare the sample mean to the population mean:
\[ z = \\frac{\\bar{x} - \\mu}{\\text{SEM}} = \\frac{92.8 - 90}{\\text{SEM}} \]
Use the z-score to determine the p-value or compare it to a critical value from the standard normal distribution to decide if the increase in reading speed is statistically significant, which will help conclude whether the new program had an effect.
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Normal Distribution
The normal distribution is a continuous probability distribution characterized by a symmetric, bell-shaped curve defined by its mean and standard deviation. It models many natural phenomena, including reading speeds, allowing us to calculate probabilities and make inferences about data relative to the mean.
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Finding Z-Scores for Non-Standard Normal Variables
Sampling Distribution of the Sample Mean
The sampling distribution of the sample mean describes the distribution of means from all possible samples of a given size drawn from a population. It is normally distributed (or approximately so for large samples) with a mean equal to the population mean and a standard error equal to the population standard deviation divided by the square root of the sample size.
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Hypothesis Testing and Statistical Significance
Hypothesis testing evaluates whether observed sample data provide enough evidence to reject a null hypothesis about a population parameter. By comparing the sample mean to the population mean using the standard error, we determine if the difference is statistically significant or likely due to random chance.
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Step 2: Calculate Test Statistic
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