rue/False 2 pts. each: 20 pts. total). Write True\' or False\' in the left margi
ID: 2906737 • Letter: R
Question
rue/False 2 pts. each: 20 pts. total). Write True' or False' in the left margin next to the question number Using n-1 rather than n in computing the sample variance makes the sample variance a better estimate of the population variance The closer r is to 1, the weaker is the linear association between the variables Randomly assigning subjects to groups in an experiment helps to balance the groups on known nown to the variables but does not help balance the groups on lurking variables that may be unk researcher The number of hours spent watching television during a week is an example of a categorical variable Of the common measures of central tendency, the mean is the least sensitive to extreme values If two variables have a positive correlation, we know that a simple regression between the two wil result in a positive slope coefficient the random variable is When finding the mean of a discrete distribution, each possible value of weighted according to its probability tandard error The standard deviation of a sampling distribution is known as the s annot exceed 1, probabilities of compound events can be Although probabilities of simple events c greater than 1. of the observations in a collected A sampling distribution is the distribution of the values of all sample of dataExplanation / Answer
a) False, as sample size increases the quality of estimate also increases.
b) False, because correlation coefficient (r) measures the extent of linear relationship between the variables. So larger the value of r stronger is the linear association.
c)True
d)False, categorical variable only contains data which can be categorised among certain levels.
e) False, among all the central tendencies median is least sensitive to extreme values.
f)True
g) True, because mean is nothing but expectation of random variable.
h)True
I) False, probability can never exceed one.
j)False, sampling distribution is the distribution of sample statistics.
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