Decoding Z-Score Chart Accuracy

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Homework Help Overview

The discussion revolves around understanding the accuracy of a Z-score chart and its application in finding critical values for statistical confidence intervals. Participants are examining how to interpret values from the chart and the relationship between probabilities and Z-scores.

Discussion Character

  • Conceptual clarification, Assumption checking, Mathematical reasoning

Approaches and Questions Raised

  • Participants are exploring how to derive the Z-score from the chart, questioning the method of finding alpha, and discussing the interpretation of the values in the context of probabilities. There is confusion regarding the conversion of probabilities to Z-scores and the rounding of values.

Discussion Status

The discussion is active, with participants providing different interpretations of the Z-score chart and how to extract values from it. Some guidance has been offered regarding the calculation of probabilities and the relationship between Z-scores and confidence levels, but there is no explicit consensus on the interpretation of specific values.

Contextual Notes

Participants are referencing a specific chart from a textbook and a solutions manual, indicating a potential reliance on external resources. There is also a mention of rounding values, which may affect the understanding of the Z-score interpretation.

60051
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I made sure this chart is identical to the one in my textbook, so there are no discrepancies.

So in the solutions manual, they find alpha by subtracting the confidence coefficient from 1, then dividing that value by 2, and looking up that value in the table.

So for one example, they used that chart and found that z0.025 = 1.96. I just don't see this though. If you look up 0.025 in the chart, you get 0.1985. In fact, all the values in the chart are decimals, so how did they get 1.96?
 
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The table is one of probabilities P(0 <= z <= n.nn), where n.n is one of the numbers down the left column and 0.0n is a number across the top row.

z0.025 is the z score for which the probability that z > some number is 0.025. Another way to say this is that the probability (or area) in the "tail" is 0.025. This means that the remaining probability is 0.975. Since the table gives probabilities for z values that are greater than or equal to 0, the probability you want is 0.475.

Look in the body of the table for 0.475. You will find this in the row that is marked 1.9, and in the column marked 0.06. What this is telling you is that P(0 <= z <= 1.96) = 0.475, or equivalently, P(z > 1.96) = 0.025.
 
How did you get 0.475? 0.95/2?
 
That will work, but you can also subtract .025 from .500.
 
60051 said:
I made sure this chart is identical to the one in my textbook, so there are no discrepancies.

So in the solutions manual, they find alpha by subtracting the confidence coefficient from 1, then dividing that value by 2, and looking up that value in the table.

So for one example, they used that chart and found that z0.025 = 1.96. I just don't see this though. If you look up 0.025 in the chart, you get 0.1985. In fact, all the values in the chart are decimals, so how did they get 1.96?
??They rounded off to two decimal places!
 
HoI, I think you missed that decimal point. If you round 0.1985 to two decimal places, you 0.20, not 1.96. My explanation is in post 2.
 

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