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astraxan [27]
3 years ago
9

9.A standard IQ test produces normally distributed results with a mean of 100 and a standard deviation of 15. A class of high sc

hool science students is grouped homogeneously by excluding students with IQ scores in either the top 15% or the bottom 15%. Find the lowest and highest possible IQ scores of students remaining in the class.(7)
Mathematics
1 answer:
Stella [2.4K]3 years ago
3 0

Answer:

The lowest possible IQ scores of students remaining in the class is 84.46.

The highest possible IQ scores of students remaining in the class is 115.54.

Step-by-step explanation:

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Mean of 100 and a standard deviation of 15.

This means that \mu = 100, \sigma = 15

Find the lowest and highest possible IQ scores of students remaining in the class.

Lowest:

The 15th percentile, which is X when Z has a pvalue of 0.15, so X when Z = -1.036.

Z = \frac{X - \mu}{\sigma}

-1.036 = \frac{X - 100}{15}

X - 100 = -1.036*15

X = 84.46

Highest:

The 100 - 15 = 85th percentile, which is X when Z has a pvalue of 0.85, so X when Z = 1.036.

Z = \frac{X - \mu}{\sigma}

1.036 = \frac{X - 100}{15}

X - 100 = 1.036*15

X = 115.54

The lowest possible IQ scores of students remaining in the class is 84.46.

The highest possible IQ scores of students remaining in the class is 115.54.

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Answer:

Step-by-step explanation:

Hello!

The objective is to test if the courses emphasize memorizing facts, ideas or methods following the same distribution as before.

The variable of interest is

X: Opinion of students in how much of their coursework emphasized memorizing facts, ideas, or methods. Categorized: 1_"Very little", 2_" Some", 3_" Quite a bit" and 4_"Very much"

It is known for a survey made in 2014 that the percentages for each category are: 1_Very little: 21.5%, 2_Some: 33.7%, 3_Quite a bit: 27.7% and 4_Very much: 17.1%

To test if the current situation follows the same distribution as the historical data (from 2014) you have to conduct a Goodness to Fit Chi-Square test.

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X^2= sum[\frac{(O:i-E_i)^2}{E_i} ]~~X^2_{k-1}

k= number of categories of the variable.

This test is always one-tailed (right), which means that you will reject the null hypothesis to high values of X² (when the observed and expected frequencies for each category are too different)

The critical value is:

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You will reject the null hypothesis if X^2_{H_0} \geq  11.345

You will not reject the null hypothesis if X^2_{H_0} < 11.345

Before calculating the statistic under the null hypothesis, you have to calculate the expected value for each category following the formula:

E_i= n*P_i

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E₂= n*P₂= 400*0.337= 134.8

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X^2_{H_0}= (\frac{(39-86)^2}{86} )+(\frac{(139-134.8)^2}{134.8} )+(\frac{(148-110.8)^2}{110.8} )+(\frac{(74-68.4)^2}{68.4} )= 38.76

As said before, this test is one-tailed to the right (always) and so is its p-value:

P(X₃²≥38.76)= 1 - P(X²₃<38.76)= 1 - 1 ≅ 0

p-value < 0.00001

Using both approaches (p-value and critical value) the decision is to reject the null hypothesis.

With a level of significance of 1% the decision is to reject the null hypothesis, then the actual courses do not emphasize the memorization of facts, ideas, and methods following the historical percentages.

I hope this helps!

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