Question: Read Chapter 5 Please respond to all questions. 1) What are the easiest and hardest concepts in the chapter? Explain your answer. 2) Why are

Read Chapter 5

Please respond to all questions.

1) What are the easiest and hardest concepts in the chapter? Explain your answer.

2) Why are Z scores important and how are they used?

Helpful Video: https://www.khanacademy.org/math/ap-statistics/density-curves-normal-distribution-ap/measuring-position/v/z-score-introduction

Chapter 5. z-Scores: Location of Scores and Standardized Distributions

Figure 5.1.

An example of a perceptual speed task. The participant is asked to search through the display as quickly as possible and circle each pair of digits that add up to 10.

6423193119463191838282461987
1142948764441955824657983946
7873726663716742627345226299
7391523755979151442346649762
9731214993918946738255981256
7382375589837327838273469762
5796465546191367732658643273
2394665591736773825564624639
8711997356736373918263331688
1942629112823292734668191164
9391328263914646365519926271

Suppose that you took Ackerman and Beier's test and your combined time and errors produced a score of 92. How did you do? Are you faster than average, fairly normal in perceptual speed, or does your score indicate a serious deficit in cognitive skill? The answer is that you have no idea how your score of 92 compares with scores for others who took the same test. Now suppose that you are also told that the distribution of perceptual speed scores has a mean of =86.75 and a standard deviation of =10.50 . With this additional information, you should realize that your score (X=92) is somewhat higher than average but not an exceptionally high score.

In this chapter we introduce a statistical procedure for converting individual scores into z-scores, so that each z-score is a meaningful value that identifies exactly where the original score is located in the distribution. As you will see, z-scores use the mean as a reference point to determine whether the score is above or below average. A z-score also uses the standard deviation as a yardstick for describing how much an individual score differs from average. For example, a z-score will tell you if your score is above the mean by a distance equal to two standard deviations, or below the mean by one-half of a standard deviation. A good understanding of the mean and the standard deviation will be a valuable background for learning about z-scores.

5.1. Introduction to z-ScoresLearning Objective

  1. Describe the two general purposes for transforming X values into z-scores.

In the previous two chapters, we introduced the concepts of the mean and standard deviation as methods for describing an entire distribution of scores. Now we shift attention to the individual scores within a distribution. In this chapter, we introduce a statistical technique that uses the mean and the standard deviation to transform each score (X value) into a z-scoreor a standard score. The purpose of z-scores, or standard scores, is to identify and describe the exact location of each score in a distribution.

The following example demonstrates why z-scores are useful and introduces the general concept of transforming X values into z-scores.

Read Chapter 5Please respond to all questions.1) What are the easiest andhardest concepts in the chapter? Explain your answer.2) Why are Z scoresimportant and how are they used?Helpful Video: https://www.khanacademy.org/math/ap-statistics/density-curves-normal-distribution-ap/measuring-position/v/z-score-introductionChapter 5. z-Scores: Location ofScores and Standardized DistributionsFigure 5.1.An example of a perceptual speed task. Theparticipant is asked to search through the display as quickly as possibleand circle each pair of digits that add up to 10.64231931194631918382824619871142948764441955824657983946787372666371674262734522629973915237559791514423466497629731214993918946738255981256738237558983732783827346976257964655461913677326586432732394665591736773825564624639871199735673637391826333168819426291128232927346681911649391328263914646365519926271Suppose thatyou took Ackerman and Beier's test and your combined time and errorsproduced a score of 92. How did you do? Are you fasterthan average, fairly normal in perceptual speed, or does your score indicatea serious deficit in cognitive skill? The answer is that you haveno idea how your score of 92 compares with scores for otherswho took the same test. Now suppose that you are also toldthat the distribution of perceptual speed scores has a mean of =86.75and a standard deviation of =10.50 . With this additional information, youshould realize that your score (X=92) is somewhat higher than average butnot an exceptionally high score.In this chapter we introduce a statistical procedurefor converting individual scores into z-scores, so that each z-score is ameaningful value that identifies exactly where the original score is located inthe distribution. As you will see, z-scores use the mean as areference point to determine whether the score is above or below average.A z-score also uses the standard deviation as a yardstick for describinghow much an individual score differs from average. For example, a z-scorewill tell you if your score is above the mean by adistance equal to two standard deviations, or below the mean by one-halfof a standard deviation. A good understanding of the mean and thestandard deviation will be a valuable background for learning about z-scores.5.1. Introductionto z-ScoresLearning ObjectiveDescribe the two general purposes for transforming X values intoz-scores.In the previous two chapters, we introduced the concepts of the meanand standard deviation as methods for describing an entire distribution of scores.Now we shift attention to the individual scores within a distribution. Inthis chapter, we introduce a statistical technique that uses the mean andthe standard deviation to transform each score (X value) into a z-scoreora standard score. The purpose of z-scores, or standard scores, is toidentify and describe the exact location of each score in a distribution.Thefollowing example demonstrates why z-scores are useful and introduces the general conceptof transforming X values into z-scores. 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