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Tanya [424]
3 years ago
13

A researcher wants to determine if there is a relationship between media outlet (social media, newspapers, and radio) and intere

st in media by population group (youth, young adults, and older adults). What type of statistical test should be used?
a. Correlation Analysisb. Independent t-testc. Dependent t-testd. ANOVAe. Chi Square
Mathematics
2 answers:
Feliz [49]3 years ago
8 0

Answer:

The researcher should use correlation analysis for his studies.

Step-by-step explanation:

What is correlation?

Correlation is a statistical tool used to quantify the degree to which two variables are related. Through the correlation analysis, you evaluate correlation coefficient that tells you how much one variable changes when the other one does. Correlation analysis provides you with a linear relationship between two.

Types of correlation

1. Positive, Negative or Zero Correlation:

2. Linear or Curvilinear Correlation:

3. Scatter Diagram Method:

4. Pearson's Product Moment

Coefficient of Correlation:

5. Spearman's Rank Correlation

Coefficient:

Elena L [17]3 years ago
8 0

Answer:

The correct option is;

e. Chi-Square

Step-by-step explanation:

From the question, the researcher is trying to find out the relationship between a large population group (social media, newspapers, and radio) and another large population group, the interest in media by population group (youths and adults) of which the data that can be collected will be mutually exclusive with independent variable and raw with an aim to present the expectation side by side with the actual observed results.The most appropriate statistical test that should be used therefore is the Chi Square test.

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A rectangular prism has volume 4,800 cubic yards, length 20 yards, and height 40 yards. Find its width, in yards.​
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HELP ASAP Calculate the residuals for your scatterplot in step 2d.
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The residuals of the linear regression equation are -1.36, 0.32, 0.01, 0.62, 0.17, -0.24, 0.89, 0.09, 0.18 and -0.7

<h3>How to determine the residuals?</h3>

The regression equation is given as:

y = 0.141x + 0.842

Next, we calculate the predicted values (y) at the corresponding x values.

So, we have:

y = 0.141 * 13.8 + 0.842 = 2.78

y = 0.141 * 18 + 0.842 = 3.38

y = 0.141 * 16.7 + 0.842 = 3.20

y = 0.141 * 18 + 0.842 = 3.38

y = 0.141 * 0.7 + 0.842 = 0.94

y = 0.141 * 21.9 + 0.842 = 3.93

y = 0.141 * 15.5 + 0.842 = 3.03

y = 0.141 * 9.2 + 0.842 = 2.14

y = 0.141 * 19.5 + 0.842 = 3.59

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Residual = Actual value - Predicted value

So, we have:

Residual = 1.42 - 2.78 = -1.36

Residual = 3.7 - 3.38 = 0.32

Residual = 3.21 - 3.20 = 0.01

Residual = 4 - 3.38 = 0.62

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Residual = 3.92 - 3.03 = 0.89

Residual = 2.23 - 2.14 = 0.09

Residual = 3.77 - 3.59 = 0.18

Residual = 2.5 - 3.20 = -0.7

Hence, the residuals of the linear regression equation are -1.36, 0.32, 0.01, 0.62, 0.17, -0.24, 0.89, 0.09, 0.18 and -0.7

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brainly.com/question/16180255

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