Assume that the data in question 25 reflect a highly skewed interval variable.
(a) What statistics would you compute to summarize these conditions? (b) We compute them to be 14, 12, and 8.5, respectively. What conclusion about the study should you draw? (c) What conclusion would you draw about the populations produced by this experiment?
Don't know about Q 25, but I would use the median and quartiles.
To summarize the conditions of a highly skewed interval variable, you would typically compute certain statistics that are appropriate for skewed data. In this case, the statistics given are 14, 12, and 8.5.
(a) To summarize the conditions, you would typically compute the following statistics:
- Measures of central tendency: These statistics help summarize the center of the data distribution. Commonly used measures of central tendency include the mean, median, and mode. In this case, you would want to compute these measures to understand the center of the data.
- Measures of dispersion: These statistics provide information about the spread or variability of the data. Commonly used measures of dispersion include the range, standard deviation, and variance. Calculating these measures would help you understand the spread of the data.
- Skewness: Skewness is a measure of the asymmetry of the data distribution. Positive skewness indicates a tail on the right side of the distribution, while negative skewness indicates a tail on the left side. Computing skewness would help you identify the direction and magnitude of the skew in the data.
(b) The given statistics of 14, 12, and 8.5 do not provide enough information to draw a conclusion about the study. These statistics could correspond to any of the measures mentioned above, and without further context, it is difficult to determine the implications of these specific values.
(c) Based solely on the given statistics, it is not possible to draw a conclusion about the populations produced by this experiment. In order to draw meaningful conclusions about populations, additional information and analyses would be needed, such as a hypothesis test, confidence intervals, or comparisons to other populations.