Describing Numerical Variables Central Michigan Universit描述变量的数值密歇根中央大学.pptVIP

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Describing Numerical Variables Central Michigan Universit描述变量的数值密歇根中央大学.ppt

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Describing Numerical Variables Central Michigan Universit描述变量的数值密歇根中央大学

Describing Numerical Variables Examining each numerical variable in your analysis Numerical Variables Variables measured with meaningful numerical values. Ratio True zero (ex., weight, height, age) Interval equal interval between values but no true zero point (ex., sociological or psychological scales) Discrete Values can only take whole numbers as values Continuous Values have no real breaking point Have infinite number of possible values Univariate Analyses with Numerical Variables Measures of Central Tendency Mean – the arithmetic average Mode – the most popular/common value of response Median – the value at which 50% of the cases lie above or below Measures of Dispersion Range – the distance between the highest and lowest value in the variable. Include minimum and maximum value of variable. Variance – how much values for a variable vary from the mean. Sum of the squared deviations from the mean Standard Deviation – the square root of the variance is typically used to evaluate the dispersion of cases around the mean. Skewness – how evenly/symmetrically the cases are distributed around the mean. Steps for Conducting a univariate analysis of numerical variables Calculate the range. Order all of the cases for your numerical data from hi to low values. Take the maximum value and subtract from it the minimum value. The result is the range. Calculate the mean. Sum together the values for all cases and then divide by the total number of cases (?(xi – X)/n) Calculate the median Ordered cases from high to low. It is the point value where half the cases lie above and half below it. Steps for Conducting a univariate analysis of numerical variables Calculate the mode. Ordered cases from high to low, select the most common value. Calculate the variance For each case, take the value and subtract the mean from it. Take this result and square it. Take and sum the squared deviations for all cases of the variable. Divide the result by the number of cases. (?(xi –