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zmey [24]
3 years ago
15

PLEASE HELP ME ON THIS MATH PROBLEM! I need an explanation

Mathematics
1 answer:
saul85 [17]3 years ago
6 0

Answer:

s. -30

Step-by-step explanation:

All the angles in a triangle equal 180 so:

-2x - x + 90 = 180

add like terms

-3x + 90 = 180

subtracts 90 from both sides

-3x = 90

divide both sides by -3

x = -30

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Open source textbook. A professor using an open source introductory statistics book predicts that 60% of the students will purch
Lostsunrise [7]

Answer:

Step-by-step explanation:

Hello!

The variable of interest is

X: Format of the statistics book the students used, categorized: "A: bought the book", "B: print the book" and "C: Online format"

The professor expects the following percentages for each category:

A: Hard copy: 60%

B: Print out: 25%

C: Online copy: 15%

At the end of the semester, the professor surveyed the students and obtained the following information

From n= 126 students,

71 bought the hard copy

30 printed the book

25 read it online

The objective of the professor is to test if the observed data follows the percentages he expected. The best way to analyze this is through a Goodness to Fit Chi-Square test.

a) The hypotheses are:

H₀: P(A)= 0.60; P(B)= 0.25; P(C)= 0.15

H₁: The observed frequencies don't adjust to the theoretical model

α: 0.05

b) For this test you can calculate the expected frequencies for each variable using the formula:

E_i= n* P_i

E_A= n * P_A= 126*0.60= 75.6\\

E_B= n * P_B= 126*0.25= 31.5

E_C= n * P_C= 126* 0.15= 18.9

Note, if the expected frequencies for all the variables are calculated corrrectly then ∑Ei= n, in this case

75.6+31.5+18.9= 126 ⇒ Is a quick way to check if the calculatios are well done, especially when you are working with more categories.

c) The conditions for this test are:

-All observartions should be independent

-The expected frequencies for all categories should be greater than 5

Ei>5

d) The statistic is:

X^2= sum \frac{(O_i-E_i)^2}{E_i} ~~X^2_{k-1}

k= number of categories of the variable

X^2_{H_0}= \frac{(71-75.6)^2}{75.6} +\frac{(30-31.5)^2}{31.5} +\frac{(25-18.9)^2}{18.9}= 2.32

This test is always one-tailed to the right, wich means that you will reject the null hypothesis to big values of X²

The critical value is X^2_{k-1;1-\alpha }= X^2_{2;0.95}= 4.303

The rejection regios is X^2_{H_0} \geq  4.303

The p-value for this test is also one-tailed to the right:

P(X₂²≥2.32)= 1 - P(X₂²<2.32)= 1 - 0.6866 = 0.3134

e) The decision rule using the p-value approach is:

If p-value ≥ α, the decision is to reject the null hypothesis.

If the p-value < α, the decision is to not reject the null hypothesis.

In this case the p-value: 0.3134 is less than the significance level I've selected α: 0.05, so the decision is to not reject the null hypothesis.

Using a level of significance of 5%, there is no significant evidence to reject the null hypothesis. Then you can conclude that the book format the students choose to use for the introductory statistics course follows the theoretical percentages expected by the professor.

I hope this helps!

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