Descriptive And Inferential Statistics Quiz

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| By Kasturi Chaudhuri
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  • 1/10 Questions

    What is the main difference between descriptive and inferential statistics?

    • Descriptive statistics summarize data, while inferential statistics make predictions.
    • Descriptive statistics make predictions, while inferential statistics summarize data.
    • Both A and B
    • None of the above
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About This Quiz

Ready to test your knowledge of statistics? Take our Descriptive and Inferential Statistics Quiz to brush up on your understanding of data analysis. Whether you're a beginner or an expert, this quiz covers the basics and beyond. Learn about descriptive statistics, which summarize data, and inferential statistics, which draw conclusions from data.
In this quiz, you'll encounter questions related to both descriptive and inferential statistics, covering various topics such as measures of central tendency, dispersion, probability distributions, hypothesis testing, and more. Descriptive statistics involve organizing, summarizing, and presenting data in a meaningful way, providing insights into the characteristics of a dataset. On the other hand, inferential statistics allow you to draw conclusions or make predictions about a population based on a sample of data.

Descriptive And Inferential Statistics Quiz - Quiz

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  • 2. 

    What does a confidence interval in inferential statistics indicate?

    • The probability that a population parameter will fall between two set values

    • It summarizes the data.

    • Both A and B

    • None of the above

    Correct Answer
    A. The probability that a population parameter will fall between two set values
    Explanation
    A confidence interval gives an estimated range of values which is likely to include an unknown population parameter. It provides an interval estimate of a population parameter rather than a point estimate. The confidence interval quantifies the level of uncertainty around the estimate of the parameter.

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  • 3. 

    What is a Type II error in hypothesis testing?

    • Rejecting a true null hypothesis

    • Not rejecting a false null hypothesis

    • Both A and B

    • None of the above

    Correct Answer
    A. Not rejecting a false null hypothesis
    Explanation
    A Type II error occurs when the null hypothesis is false, but erroneously fails to be rejected. It is failing to assert what is present, a miss. While a Type I error is a false positive, a Type II error is a false negative.

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  • 4. 

    What is the role of standard deviation in descriptive statistics?

    • It measures the amount of variation or dispersion in a set of values.

    • It is used for hypothesis testing.

    • Both A and B

    • None of the above

    Correct Answer
    A. It measures the amount of variation or dispersion in a set of values.
    Explanation
    Standard deviation is a measure of the amount of variation or dispersion of a set of values. A low standard deviation indicates that the values tend to be close to the mean of the set, while a high standard deviation indicates that the values are spread out over a wider range.

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  • 5. 

    What is the purpose of a p-value in inferential statistics?

    • To determine the significance of results

    • To summarize the data

    • Both A and B

    • None of the above

    Correct Answer
    A. To determine the significance of results
    Explanation
    The p-value is a statistical concept that provides a measure of the evidence against the null hypothesis. It is used in hypothesis testing to help you support or reject the null hypothesis. The p-value represents the probability that the results of your test occurred at random. If the p-value is small, one rejects the null hypothesis.

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  • 6. 

    What is the null hypothesis in inferential statistics?

    • A statement that there is no effect or relationship between variables

    • A statement that there is an effect or relationship between variables

    • Both A and B

    • None of the above

    Correct Answer
    A. A statement that there is no effect or relationship between variables
    Explanation
    The null hypothesis is a general statement or default position that there is no relationship between two measured phenomena, or no association among groups. It is the hypothesis that the researcher seeks to disprove, reject or nullify.

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  • 7. 

    What is a Type I error in hypothesis testing?

    • Rejecting a true null hypothesis

    • Not rejecting a false null hypothesis

    • Both A and B

    • None of the above

    Correct Answer
    A. Rejecting a true null hypothesis
    Explanation
    A Type I error occurs when the null hypothesis is true, but is rejected. It is asserting something that is absent, a false hit. A Type I error is often considered to be more serious, and therefore more important to avoid, than a Type II error.

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  • 8. 

    What is the role of the Z-score in inferential statistics?

    • It indicates how many standard deviations an element is from the mean.

    • It is used for hypothesis testing.

    • Both A and B

    • None of the above

    Correct Answer
    A. It indicates how many standard deviations an element is from the mean.
    Explanation
    A Z-score is a numerical measurement that describes a value’s relationship to the mean of a group of values. It is a measure of how many standard deviations an element is from the mean. It can be placed on a normal distribution curve.

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  • 9. 

    What does correlation measure in inferential statistics?

    • The strength and direction of the linear relationship between two variables

    • The causal relationship between two variables

    • Both A and B

    • None of the above

    Correct Answer
    A. The strength and direction of the linear relationship between two variables
    Explanation
    Correlation is a statistical measure that expresses the extent to which two variables are linearly related. It ranges from -1 to 1, with -1 indicating a perfect negative correlation, +1 indicating a perfect positive correlation, and 0 indicating no correlation at all. It gives us a measure of the strength and direction of the relationship between two variables.

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  • 10. 

    What is a common graphical representation method in descriptive statistics?

    • Histogram

    • Pie chart

    • Both A and B

    • None of the above

    Correct Answer
    A. Both A and B
    Explanation
    Histograms and pie charts are common methods of displaying data in descriptive statistics. A histogram is a graphical representation that organizes a group of data points into a specified range, showing the data’s distribution. Pie charts, on the other hand, are circular charts divided into sectors or ‘pie slices’, usually illustrating numerical proportion.

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Quiz Review Timeline (Updated): Mar 22, 2024 +

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  • Current Version
  • Mar 22, 2024
    Quiz Edited by
    ProProfs Editorial Team
  • Mar 21, 2024
    Quiz Created by
    Kasturi Chaudhuri
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