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Understanding Research Findings quiz

컨트롤 버튼이 '내비게이션' 모드로 변경되었습니다.
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  • What are the three measures of central tendency used to summarize typical values in a dataset?
    The three measures are mean, median, and mode.
  • How is the mean calculated in a dataset?
    The mean is calculated by adding up all values and dividing by the number of values.
  • What does the median represent in a dataset?
    The median is the middle value when all numbers are arranged in numerical order.
  • How do you determine the mode in a dataset?
    The mode is the value that occurs most frequently in the dataset.
  • Why are means sensitive to outliers?
    Means are sensitive because outliers can artificially inflate or deflate the average.
  • Which measure of central tendency is resistant to outliers?
    The median is resistant to outliers and is not affected by extreme values.
  • Can a dataset have more than one mode or no mode at all?
    Yes, a dataset can have multiple modes or no mode if all values occur only once.
  • What is a correlation in sociological research?
    A correlation is a relationship in which two variables change together.
  • What does the correlation coefficient 'r' indicate?
    The coefficient 'r' quantifies the direction and strength of the relationship between two variables.
  • What is the difference between a positive and negative correlation?
    Positive correlation means variables change in the same direction; negative means they change in opposite directions.
  • What does an r value of zero mean?
    An r value of zero means there is no correlation between the variables.
  • How is the strength of a correlation interpreted using the r value?
    The closer r is to ±1, the stronger the correlation; values near zero indicate weak or no correlation.
  • Does correlation imply causation in sociological research?
    No, correlation does not imply causation; further evidence is needed to establish causality.
  • What are the requirements for establishing causality between variables?
    Researchers must show correlation, temporal precedence, and rule out spurious correlations.
  • What is a spurious correlation?
    A spurious correlation is a relationship between two variables caused by a third, unaccounted-for variable.