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STAT 121 FINAL EXAM QUESTIONS WITH VERIFIED ANSWERS

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STAT 121 FINAL EXAM QUESTIONS WITH VERIFIED ANSWERS

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STAT 121 FINAL EXAM QUESTIONS WITH VERIFIED
ANSWERS


statistical population - Answers - All possible sampling units
Eg: All UMBC students if measuring height of UMBC students.

sampling frame - Answers - a list of individuals from whom the sample is drawn (eg: 500
UMBC students)

sample - Answers - a representative segment of a target population (the 350 UMBC
students who actually reply)

Completely randomized - Answers - an experimental design is when all units are
allocated at random among the treatments

randomized block - Answers - Subjects first assigned to block according to attribute (ie
sex, ethnicity) then randomized to treatment group (eg: male vs female UMBC student
height)

Matched Pairs - Answers - an observational technique that involves matching each
participant in the experimental group with a specific participant in the control group in
order to eliminate the possibility that a third variable (and not the independent variable)
caused changes in the dependent variable

observational study - Answers - observes individuals and measures variables of interest
but does not attempt to influence the responses (eg: internet survey of UMBC students
and their height)

experiment - Answers - the act of conducting a controlled test or investigation (eg:
caffeine effects on UMBC students. Control group receives placebo, while experimental
group receives caffeine pill. Test physical and mental capacity after length of time)

explanatory variable - Answers - the independent variable that attempts to explain the
relationship with the other variable. It becomes the x variable on the graph

response variable - Answers - dependent variable that represents the outcome of a
change (y)

single-blind study - Answers - a study in which the participants are unaware of whether
they are in the control group or the experimental group

, double-blind study - Answers - an experiment in which neither the participant nor the
researcher knows whether the participant has received the treatment or the placebo

cluster sampling - Answers - form of sampling in which large groupings ("clusters") are
selected first (eg UMBC students), with successive subsampling of smaller units (eg
male vs female UMBC students)

stratified sampling - Answers - dividing a population into subgroups (strata) and then
taking a separate random sample from each stratum (eg: gender, race, age)

Multistage sampling - Answers - a form of cluster sampling in which clusters are further
broken down by taking samples from each cluster (eg: male vs female, black vs white,
freshman vs seniors)

Voluntary response - Answers - type of bias that is problematic because those who
volunteer tend to have strong negative or positive opinions

convenience sample - Answers - when researchers draw participants from the
populations that are readily available to them

What are some biases in studies? - Answers - volunteer responses, convenience
sampling, not having a random enough sampling frame, non-response, systematically
sampling people

lurking variables - Answers - A variable that has an important effect on the relationship
among the variables in a study but is not taken into account. (eg: smoking and
birthweight, but the LV is other possible drug use)

confounding - Answers - occurs in an experiment when you are not able to distinguish
among the effects of different factors.

mean - Answers - an average of n numbers computed by adding some function of the
numbers and dividing by some function of n (eg: data are 1,5,2,7,8. Add numbers and
divide by 5)

median - Answers - the middle number in an ordered set of data (if data are even, find
the mean of the middle 2 numbers. If odd, just find the middle number)

standard deviation - Answers - a measure of variability that describes an average
distance of every score from the mean

standard deviation equation - Answers - 1. find the mean of your data (ex. n+n+n/n=9)
2. find the deviations by subtracting the mean from each data point. (ex:n-9) 3. Square
each deviation (ex. n^2) 4. Average the square deviations up and divide them by n-1. *N
being 1 less than the sample size* 5. Take square root of averaged number = SD

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