The Chi-square Tests Assessment Test

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  • 1/10 Questions

    Contingency tables and degrees of freedom are key elements in chi-square test? 

    • False
    • Maybe
    • True
    • None
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About This Quiz

Take our assessment test to assess your knowledge of the chi-square tests. The chi-square goodness of fit test that determines if a sample data matches a population and the chi-square test for independence that compares two variables in a contingency table to see if they are related.

The Chi-square Tests Assessment Test - Quiz

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  • 2. 
    Which of these symbols is used to represent a chi-square test?    - ProProfs

    Which of these symbols is used to represent a chi-square test?   

    • C

    • Q

    • T

    • X2

    Correct Answer
    A. X2
    Explanation
    The symbol "X2" is used to represent a chi-square test. Chi-square tests are statistical tests that are used to determine if there is a significant association between two categorical variables. The "X2" symbol is derived from the Greek letter "chi" (χ) and represents the chi-square statistic, which is calculated by comparing the observed and expected frequencies in a contingency table. By comparing the calculated chi-square statistic to a critical value from the chi-square distribution, one can determine if the observed frequencies significantly differ from the expected frequencies.

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  • 3. 
    The least expected value in each contingency table cell in order for a chi-square test to be effective is... - ProProfs

    The least expected value in each contingency table cell in order for a chi-square test to be effective is...

    • 5

    • 4

    • 3

    • 2

    Correct Answer
    A. 5
    Explanation
    For a chi-square test to be effective, the expected values in each contingency table cell should not be too small. A general guideline is that the expected value in each cell should be at least 5. This ensures that the assumptions of the chi-square test are met and that the test statistic follows the chi-square distribution. Having expected values less than 5 can lead to unreliable results and low statistical power. Therefore, the least expected value in each contingency table cell for a chi-square test to be effective is 5.

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  • 4. 
    What type of data do you use for a chi-square table? - ProProfs

    What type of data do you use for a chi-square table?

    • Ratios

    • Scales

    • Ordinal

    • Categorical

    Correct Answer
    A. Categorical
    Explanation
    Chi-square tests are used to analyze categorical data, which consists of non-numerical variables that can be divided into categories or groups. Examples of categorical data include gender, race, and occupation. The chi-square table is a statistical tool that provides critical values for the chi-square test statistic, which is used to determine the significance of the relationship between two categorical variables. Therefore, the correct answer is "Categorical" as it accurately describes the type of data used for a chi-square table.

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  • 5. 
    By which other name is a chi-square contingency table analysis known? - ProProfs

    By which other name is a chi-square contingency table analysis known?

    • Chi-square test for independence

    • Chi-square test for dependence

    • Chi-square variable test

    • None of the above

    Correct Answer
    A. Chi-square test for independence
    Explanation
    A chi-square contingency table analysis is also known as a Chi-square test for independence. This test is used to determine if there is a significant association between two categorical variables. It compares the observed frequencies in each category of the variables with the expected frequencies under the assumption of independence. If the test statistic is significant, it indicates that there is a relationship between the variables. Therefore, the correct answer is Chi-square test for independence.

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  • 6. 
    How can low expected values be dealt with? - ProProfs

    How can low expected values be dealt with?

    • Add more of the same number

    • Increase the sample size or combine categories

    • Exclude outliers

    • None of these

    Correct Answer
    A. Increase the sample size or combine categories
    Explanation
    To deal with low expected values, increasing the sample size or combining categories can be effective. Increasing the sample size provides more data points, which can lead to more accurate and reliable results. Combining categories can help to increase the frequency of occurrence, making the expected values more meaningful. This approach allows for a better representation of the data and helps to reduce the impact of outliers, which may skew the results. Adding more of the same number or excluding outliers may not necessarily address the issue of low expected values.

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  • 7. 
    How many cases must appear in one category of a chi-square test?  - ProProfs

    How many cases must appear in one category of a chi-square test? 

    • 4

    • 6

    • 5

    • 7

    Correct Answer
    A. 5
    Explanation
    In a chi-square test, the number of cases that must appear in one category depends on the specific requirements of the test and the research question being investigated. However, there is no specific rule stating that a certain number of cases must appear in one category. The number of cases in each category should be determined based on the sample size, the expected frequencies, and the statistical power desired for the test. Therefore, the answer "5" is incorrect and the question may be incomplete or not readable.

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  • 8. 
    What is the null hypothesis in chi-square test? - ProProfs

    What is the null hypothesis in chi-square test?

    • The rows and columns are the same

    • The rows and columns in the table are associated

    • The rows and columns in the table are not associated

    • The rows and column are not the same

    Correct Answer
    A. The rows and columns in the table are not associated
    Explanation
    The null hypothesis in a chi-square test states that there is no association between the rows and columns in the table. In other words, the variables being analyzed are independent of each other.

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  • 9. 
    What is an effective size? - ProProfs

    What is an effective size?

    • The magnitude of the relationship between variables

    • The likelihood of type 1 and type 2 errors

    • The number of expected cases

    • The variance explained by the measures

    Correct Answer
    A. The magnitude of the relationship between variables
    Explanation
    An effective size refers to the magnitude of the relationship between variables. It measures the strength or intensity of the relationship between two or more variables. It indicates how much one variable is influenced or affected by another variable. A larger effective size indicates a stronger relationship between the variables, while a smaller effective size suggests a weaker relationship. Therefore, the effective size is a crucial measure in determining the strength and significance of the relationship between variables.

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  • 10. 
    What is another name for the chi-square goodness fit test?  - ProProfs

    What is another name for the chi-square goodness fit test? 

    • Directional chi-square   

    • One sample chi-square

    • Chi-square Anova 

    • Two sample chi-square

    Correct Answer
    A. One sample chi-square
    Explanation
    The chi-square goodness fit test is also known as the one sample chi-square test. This test is used to determine whether there is a significant difference between the observed and expected frequencies in a categorical variable. It compares the observed frequencies with the expected frequencies and calculates a chi-square statistic. By comparing this statistic to a critical value, we can determine whether the observed frequencies deviate significantly from the expected frequencies.

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  • Current Version
  • Mar 21, 2023
    Quiz Edited by
    ProProfs Editorial Team
  • Jan 10, 2018
    Quiz Created by
    Cripstwick
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