The spotlight effect refers to overestimating the extent to which others notice your appearance or behavior, especially when you commit a social faux pas. Effectively, you feel as if you are suddenly
The spotlight effect refers to overestimating the extent to which others notice your appearance or behavior, especially when you commit a social faux pas. Effectively, you feel as if you are suddenly
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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- . The spotlight effect refers to overestimating the extent to which others notice your appearance or behavior, especially when you commit a social faux pas. Effectively, you feel as if you are suddenly standing in a spotlight with everyone In one demonstration of this phenomenon, Gilovich, Medvec, and Savitsky (2000) asked college students to put on a Barry Manilow T-shirt that fellow students had previously judged to be embarrassing. The participants were then led into a room in which other students were already participating in an experiment. After a few minutes, the participant was led back out of the room and was allowed to remove the shirt. Later, each participant was asked to estimate how many people in the room had noticed the shirt. The individuals who were in the room were also asked whether they noticed the shirt. In the study, the participants significantly overestimated the actual number of people who had noticed.
- In a similar study using a sample of n = 9 participants, the individuals who wore the shirt produced an average estimate of M = 4 with SS = 162. The average number who said they noticed was 3.1. Is the estimate from the participants significantly different from the actual number? Test the null hypothesis that the true mean is µ = 3.1 using a two-tailed test with α = .05.
- Is the estimate from the participants significantly higher than the actual number (µ = 3.1 )? Use a one-tailed test with α = .05.
Because the test statistic doesn’t fall outside the critical region fail to reject the null hypothesis. We can’t conclude that the estimate from the participants significantly different from the actual number.
The null hypothesis states that the data indicate no difference between 2 conditions.
- To evaluate the effect of a treatment, a sample of n = 6 is obtained from a population with a mean of
= |
- µ, = 80, and the treatment is administered to the individuals in the After treatment, the sample mean is found to be M 72.
- If the sample variance is s2 = 54, are the data sufficient to conclude that the treatment has a significant effect using a two-tailed test with α= .05?
- If the sample variance is s2 = 150, are the data sufficient to conclude that the treatment has a significant effect using a two-tailed test with α= .05?
- To evaluate the effect of a treatment, a sample is obtained from a population with a mean of µ = 20, and the treatment is administered to the individuals in the sample. After treatment, the sample mean is found to be M = 3 with a variance of s2 = 9.
- Assuming that the sample consists of n = 16 individuals, use a two-tailed hypothesis test with a = .05 to determine whether the treatment effect is significant and compute both Cohen's d and? to measure effect Are the data sufficient to conclude that the treatment has a significant effect using a two-tailed test with a = .05?
- Assuming that the sample consists of n = 36 individuals, repeat the test and compute both measures of effect
- Comparing your answers for parts a and b,how does the size of the sample influence the outcome of a hypothesis test and measures of effect size?
- Standardized measures seem to indicate that the average level of anxiety has increased gradually over the past 50 years (Twenge,2000). In the 1950s, the average score on the Child Manifest Anxiety Scale wasµ = 15.1. A sample of n = 16 of today's children produces a mean score of M = 23.3 with SS = 240.
- Based on the sample, has there been a significant change in the average level of anxiety since the 1950s? Use a two-tailed test with a = .01.
- Make a 90% confidence
interval estimate of to day's population mean level of
- Write a sentence that demonstrates how the outcome of the hypothesis test and the confidence interval would appear in a research
= = |
- Belsky, Weinraub, Owen, and Kelly (2001) reported on the effects of preschool child care on the development of young One result suggests that children who spend more time away from their mothers are more likely to show behavioral problems in kindergarten. Using a standardized scale, the aver age rating of behavioral problems for kindergarten children is µ, 35. A sample of n = 16 kindergarten children who had spent at least 20 hours per week in child care during the previous year produced a mean score of M = 42.7 with a standard deviation of s = 6.
- Are the data sufficient to conclude that children with a history of child care show significantly more behavioral problems than the average kindergarten child? Use a one-tailed test with α = .01.
- Compute the 90% confidence interval for the mean rating of behavioral problems for the population of kindergarteners who have a history if child care.
- Writ a sentence showing how the outcome and hypothesis would appear in a research report.
kindergarten children who have a history of child care.
- Write a sentence showing how the outcome of the hypothesis test and the confidence interval would appear in a research report.
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