POS 3713 FINAL EXAM QUESTIONS & ANSWERS
Measurement Reliability - Answers -Repeat a measurement and yield the same results,
e.g bathroom scale weighs the same the first and second weighing
Measurement Validity - Answers -A measurement accurately represents the concept
that it is supposed to measure
Categorical Variables - Answers -Variables that cannot be ranked, put in order, or have
any measured value. E.g. Religious classification
Ordinal Variables - Answers -Variables that are categories, but can be ranked or
chronicled. E.g. Ranking satisfactions: Much better, somewhat better, same, somewhat
worse, worse etc.
Continuous Variables - Answers -Variables that have equal units of difference, usually
containing a number value
Central Tendency - Answers -Describes the distribution of variables; mean, median and
mode
Mode - Answers -The most
Median - Answers -Exact middle of the distribution
Dispersion - Answers -The measure of the spread of values; E.g. IQR and Standard
Deviation
Mean - Answers -The average
Zero-Sum Property - Answers -When the differences of the mean added together from
a distribution equals zero
The Sum of: Yi-Ybar = 0
Least-Squares Property - Answers -The sum of the squared differences between each
value of Y and the mean value of Y is less than the sum of squared differences between
each value of Y, and any number that is not the mean value of Y.
Variance - Answers -The sum of the differences of the mean, squared, divided by the
sample number minus 1
[(Yi-Ybar)^2]/n-1
, Standard Deviation - Answers -- Average difference between values of Y and the mean
value of Y
- Square root of variance
Statistical Inference - Answers -We use what we know to be true about one thing (the
sample) to deduce what is likely to be true about another thing (the population)
In other words, setting up a sample as a representation for the population
Central Limit Theorem - Answers -For an infinite number of random samples from a
population, the sample means will be distributed normally, or will produce a normal
distribution
68-95-99 Rule - Answers -Confidence intervals, percentage of certainty the data will fall
in that dispersion from the mean
1 standard error, 2 standard error, 3 standard error
Confidence Interval - Answers -The certainty of the likely location of the population
mean
Relationships Between Sample Size and Confidence Intervals - Answers -The greater
the sample size, the smaller the distribution of data will be
P-values - Answers -Ranges between 0 and 1, is the probability that we would see the
relationship that we are finding because of random chance.
Statistical Significance - Answers -The test result is above the critical value
Chi Squared Test - Answers -[(O-E)]^2/E
Difference of Means Test - Answers -[(Standard Deviation1^2)/(n)#observations1] +
[(S2^2)/n2]
Covariance - Answers -(Differences of means of X)(Differences of Means of Y)/n
Summarizing the general pattern of association between two variables and determining
if it's positive or negative
Correlation Coefficient (Pearson's r) - Answers -Covariance standardized, whichever
calculation is closest to - or + 1 is the strongest correlation
Covariance of x and y/the square root of the variance of x * the variance of y
Residuals/errors - Answers -Differences between the points on the graph and the best
fit line
Measurement Reliability - Answers -Repeat a measurement and yield the same results,
e.g bathroom scale weighs the same the first and second weighing
Measurement Validity - Answers -A measurement accurately represents the concept
that it is supposed to measure
Categorical Variables - Answers -Variables that cannot be ranked, put in order, or have
any measured value. E.g. Religious classification
Ordinal Variables - Answers -Variables that are categories, but can be ranked or
chronicled. E.g. Ranking satisfactions: Much better, somewhat better, same, somewhat
worse, worse etc.
Continuous Variables - Answers -Variables that have equal units of difference, usually
containing a number value
Central Tendency - Answers -Describes the distribution of variables; mean, median and
mode
Mode - Answers -The most
Median - Answers -Exact middle of the distribution
Dispersion - Answers -The measure of the spread of values; E.g. IQR and Standard
Deviation
Mean - Answers -The average
Zero-Sum Property - Answers -When the differences of the mean added together from
a distribution equals zero
The Sum of: Yi-Ybar = 0
Least-Squares Property - Answers -The sum of the squared differences between each
value of Y and the mean value of Y is less than the sum of squared differences between
each value of Y, and any number that is not the mean value of Y.
Variance - Answers -The sum of the differences of the mean, squared, divided by the
sample number minus 1
[(Yi-Ybar)^2]/n-1
, Standard Deviation - Answers -- Average difference between values of Y and the mean
value of Y
- Square root of variance
Statistical Inference - Answers -We use what we know to be true about one thing (the
sample) to deduce what is likely to be true about another thing (the population)
In other words, setting up a sample as a representation for the population
Central Limit Theorem - Answers -For an infinite number of random samples from a
population, the sample means will be distributed normally, or will produce a normal
distribution
68-95-99 Rule - Answers -Confidence intervals, percentage of certainty the data will fall
in that dispersion from the mean
1 standard error, 2 standard error, 3 standard error
Confidence Interval - Answers -The certainty of the likely location of the population
mean
Relationships Between Sample Size and Confidence Intervals - Answers -The greater
the sample size, the smaller the distribution of data will be
P-values - Answers -Ranges between 0 and 1, is the probability that we would see the
relationship that we are finding because of random chance.
Statistical Significance - Answers -The test result is above the critical value
Chi Squared Test - Answers -[(O-E)]^2/E
Difference of Means Test - Answers -[(Standard Deviation1^2)/(n)#observations1] +
[(S2^2)/n2]
Covariance - Answers -(Differences of means of X)(Differences of Means of Y)/n
Summarizing the general pattern of association between two variables and determining
if it's positive or negative
Correlation Coefficient (Pearson's r) - Answers -Covariance standardized, whichever
calculation is closest to - or + 1 is the strongest correlation
Covariance of x and y/the square root of the variance of x * the variance of y
Residuals/errors - Answers -Differences between the points on the graph and the best
fit line
