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Question
define the term statistical significance. a measure that shows how much variation is in a data set the variable that changes, depending on the changes in the independent variable a measure of how meaningful the data is the variable that is purposefully changed in an experiment 2) choose all that apply. which three things does statistical significance tell us about data? whether or not the results are 100% accurate whether or not the results are from error whether or not the results are from chance whether or not the results are biased whether or not the results from the sample can be applied to the population 3) choose the best answer. what does the standard deviation show? the mode of a data set the mean of a data set how much variation is in a data set
Question 1: Define the term statistical significance.
- "a measure that shows how much variation is in a data set" describes measures like standard deviation, not statistical significance.
- "the variable that changes, depending on the changes in the independent variable" is the dependent variable.
- "a measure of how meaningful the data is" matches the concept of statistical significance, as it assesses if results are not due to chance and have practical meaning.
- "the variable that is purposefully changed in an experiment" is the independent variable.
- "whether or not the results are 100% accurate": Statistical significance doesn't guarantee 100% accuracy, so this is incorrect.
- "whether or not the results are from error": Statistical significance helps determine if results are likely not due to random error.
- "whether or not the results are from chance": A key aspect of statistical significance is assessing if results are due to chance (low probability of chance explains them).
- "whether or not the results are biased": Statistical significance doesn't directly address bias (bias is about study design, sampling, etc.).
- "whether or not the results from the sample can be applied to the population": Statistical significance helps with generalizability (inferential stats) from sample to population.
So the three are: whether or not the results are from error, whether or not the results are from chance, whether or not the results from the sample can be applied to the population.
- "the mode of a data set": Mode is the most frequent value, not related to standard deviation.
- "the mean of a data set": Mean is the average, standard deviation is not the mean.
- "how much variation is in a data set": Standard deviation quantifies the amount of variation (dispersion) in a data set.
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a measure of how meaningful the data is