Fundamentals Of Statistics Ch.3

Front 1

arithmetic mean

Back 1

add all the values of the variable in the data set and dividing by the number of observations.

Front 2

population arithmetic mean

Back 2

is computed using all the individuals in a population. the population mean is a parameter.

Hint 2

Front 3

sample arithmetic mean

Back 3

is computed using sample data. the sample mean is a statistic.

Hint 3

Front 4

formulas for computing population and sample means

Back 4

population mean

Hint 4

sample mean

Front 5

median

Back 5

of a variable is the value that lies in the middle of the data when arranged in ascending order. we use M to represent the median.

Front 6

resistant

Back 6

a numerical summary of data is said to be resistant if extreme values (very large or small) relative to the data do not affect its value substantially.

Front 7

mode

Back 7

of a variable is the most frequent observation of the variable that occurs in the data set.

Front 8

dispersion

Back 8

the degree to which the data are spread out

Front 9

range, R

Back 9

the difference between the largest and the smallest data value.

Hint 9

Range=R=largest data value-smallest data value

Front 10

population standard deviation

Back 10

the square root of the sum of squared deviations about the population mean divided by the number of observations in the population , N. that is , it is the square root of the mean of the squared deviations about the population mean.

Hint 10

Front 11

sample standard deviation

Back 11

s, the square root of the sum of squared deviations about the sample mean divided by n-1 , where n is the sample size.

Hint 11

Front 12

variance

Back 12

is the square of the standard deviation. the population variance is ó^2 and the sample variance is s^2 .

Front 13

class midpoint

Back 13

the sum of consecutive lower class limits divided by 2.

Front 14

approximate mean of a variable from a frequency distribution

Back 14

Front 15

weighted mean

Back 15

multiply each value of the variable by its corresponding weight, adding these products, and dividing this sum by the sum of the weights.

Hint 15

wi is the weight of the ith observation. xi is the value of the ith observation.

Front 16

approximate standard deviation of a variable from a frequency distribution

Back 16

Hint 16

xi is the midpoint or value of the ith class

fi is the frequency of the ith class

Front 17

z-scores

Back 17

the distance that a data value is from the mean in terms of standard deviations . subtract the mean from the data value and divide the result by the standard deviation.

Hint 17