PSYC 3130 Final Exam Questions With
Verified Answers
When should you use a z-test? - ANSWER Used to test whether a sample mean is
significantly different from a population mean when we know the population
mean and standard deviation
What are the assumptions for a z-test? - ANSWER 1. We have randomly selected
one sample
2. The dependent variable is at least approximately normally distributed in the
population, it involved an interval or ratio scale, and the mean is the appropriate
measure of central tendency
3. We know the mean of the population of raw scores under some other
condition of the independent variable
4. We know the standard deviation of the population described by the null
hypothesis; it is not estimated using the sample
When should you use a single sample t-test? - ANSWER Used to test whether a
sample mean is significantly different from a population mean when we know the
population mean, but we do not know the population standard deviation
What are the assumptions for a single sample t-test? - ANSWER 1. We have one
random sample of interval or ratio scores
2. The raw score population forms of a normal distribution for which the mean is
the appropriate measure of central tendency
3. The standard deviation of the raw score population is estimated by sx
computed from our sample
When should you use a binomial test (binomial probability distribution)? -
ANSWER We use it when an experiment meets certain conditions
What are the assumptions for a binomial test (binomial probability distriubtion)?
- ANSWER 1. A single trial may result in exactly two events (called success and
failure)
2. n such trials take place (n is fixed in advance)
3. The trials are completely independent
4. The probability of a success does not change over trials (stationarity)
5. We are interested in the total number of successes occurring over the n trials
,When should you use an independent samples t-test? - ANSWER Used to test for
mean differences between two independent samples (ex: two different groups)
What are the assumptions for an independent samples t-test? - ANSWER 1. The
two random samples of scores are measured on an interval or ratio scale
2. The population of raw scores represented by each sample forms a normal
distribution, and the mean is the appropriate measure of central tendency (if
each sample n is greater than 30, the populations need only form roughly normal
distributions)
3. We do not know the variance of any raw score population and must estimate it
from the sample data
When should you use a basic 1-way ANOVA test? - ANSWER We use this as an
extension of the t-test; used when there are more than two groups
What are the assumptions for a basic 1-way ANOVA test? - ANSWER 1. The
observations are drawn from a population that is normally distributed on the
dependent variable in each group
2. There is homogeneity of variance (the variability within each group is roughly
the same)
3. The observations are independent (one score is unrelated to another score)
What is a z-score? - ANSWER a) A raw score that has been converted into
standard deviation units
b) The sum of z-scores will be 0
c) Tells us how far a score is from the mean (average)
What is a random sample? - ANSWER A sample in which every member of the
population has an equal chance of being selected
What is random assignment? - ANSWER A sample can be randomly divided into
two groups; one group is assigned to the treatment condition (drug) and the
other group is assigned to the control condition (placebo); this random division
of the sample into two groups is called random assignment
What is a population? - ANSWER A larger set of data from which a sample is
drawn
What is a sample? - ANSWER A small subset of a larger set of data
What are statistics? - ANSWER A number that describes a sample (ex: the
sample mean or sample standard deviation)
What are parameters? - ANSWER A number that describes a population (ex: the
population mean or population standard deviation)
, What are sums of squares? - ANSWER In ANOVA, the sum of squares is used to
indicate variation
How are sums of squares partitioned in ANOVA? - ANSWER ANOVA partitions
the variation into various sources:
a) Between variance (SSB) is the variance that we can explain; this variation is
due to the fact that we treated people differently (treatment conditions)
b) Within variance (SSW) is the variance that we cannot explain; we do not know
why people who were treated the same differed in their scores
What is directional hypothesis testing? - ANSWER When we use a directional
hypothesis, we are concerned with whether or not our observed differences are
in a pre-specified direction
What is nondirectional hypothesis testing? - ANSWER When we use a non-
directional hypothesis, we are concerned with whether or not our two samples,
or sample and population, differ significantly, regardless of the direction of the
difference
What is a 1-tailed statistical test? - ANSWER A test that computes the probability
of a sample mean being one or more points higher than the hypothesized mean
What type of hypothesis goes with a 1-tailed statistical test? - ANSWER We use a
directional hypothesis for a 1-tailed test
What is a 2-tailed statistical test? - ANSWER A test that computes the probability
of a sample mean differing by one or more points in either direction from the
hypothesized mean
What type of hypothesis goes with a 2-tailed statistical test? - ANSWER We use a
non-directional hypothesis for a 2-tailed test
What is type I error? - ANSWER Rejecting the null hypothesis when it is true
What is type II error? - ANSWER Not rejecting the null hypothesis when it is false
What is a sampling distribution? - ANSWER Hypothetical or theoretical
distributions of statistics (for instance, we can estimate the variability of the
difference between two means of a given sample size when the null hypothesis
is true - no difference in the population - this is the sampling distribution of the
difference between two means)
What are the 8 types of mean comparison procedures? - ANSWER 1. Linear
contrast
2. Bonferonni approach
3. Dunn-Sidak test
Verified Answers
When should you use a z-test? - ANSWER Used to test whether a sample mean is
significantly different from a population mean when we know the population
mean and standard deviation
What are the assumptions for a z-test? - ANSWER 1. We have randomly selected
one sample
2. The dependent variable is at least approximately normally distributed in the
population, it involved an interval or ratio scale, and the mean is the appropriate
measure of central tendency
3. We know the mean of the population of raw scores under some other
condition of the independent variable
4. We know the standard deviation of the population described by the null
hypothesis; it is not estimated using the sample
When should you use a single sample t-test? - ANSWER Used to test whether a
sample mean is significantly different from a population mean when we know the
population mean, but we do not know the population standard deviation
What are the assumptions for a single sample t-test? - ANSWER 1. We have one
random sample of interval or ratio scores
2. The raw score population forms of a normal distribution for which the mean is
the appropriate measure of central tendency
3. The standard deviation of the raw score population is estimated by sx
computed from our sample
When should you use a binomial test (binomial probability distribution)? -
ANSWER We use it when an experiment meets certain conditions
What are the assumptions for a binomial test (binomial probability distriubtion)?
- ANSWER 1. A single trial may result in exactly two events (called success and
failure)
2. n such trials take place (n is fixed in advance)
3. The trials are completely independent
4. The probability of a success does not change over trials (stationarity)
5. We are interested in the total number of successes occurring over the n trials
,When should you use an independent samples t-test? - ANSWER Used to test for
mean differences between two independent samples (ex: two different groups)
What are the assumptions for an independent samples t-test? - ANSWER 1. The
two random samples of scores are measured on an interval or ratio scale
2. The population of raw scores represented by each sample forms a normal
distribution, and the mean is the appropriate measure of central tendency (if
each sample n is greater than 30, the populations need only form roughly normal
distributions)
3. We do not know the variance of any raw score population and must estimate it
from the sample data
When should you use a basic 1-way ANOVA test? - ANSWER We use this as an
extension of the t-test; used when there are more than two groups
What are the assumptions for a basic 1-way ANOVA test? - ANSWER 1. The
observations are drawn from a population that is normally distributed on the
dependent variable in each group
2. There is homogeneity of variance (the variability within each group is roughly
the same)
3. The observations are independent (one score is unrelated to another score)
What is a z-score? - ANSWER a) A raw score that has been converted into
standard deviation units
b) The sum of z-scores will be 0
c) Tells us how far a score is from the mean (average)
What is a random sample? - ANSWER A sample in which every member of the
population has an equal chance of being selected
What is random assignment? - ANSWER A sample can be randomly divided into
two groups; one group is assigned to the treatment condition (drug) and the
other group is assigned to the control condition (placebo); this random division
of the sample into two groups is called random assignment
What is a population? - ANSWER A larger set of data from which a sample is
drawn
What is a sample? - ANSWER A small subset of a larger set of data
What are statistics? - ANSWER A number that describes a sample (ex: the
sample mean or sample standard deviation)
What are parameters? - ANSWER A number that describes a population (ex: the
population mean or population standard deviation)
, What are sums of squares? - ANSWER In ANOVA, the sum of squares is used to
indicate variation
How are sums of squares partitioned in ANOVA? - ANSWER ANOVA partitions
the variation into various sources:
a) Between variance (SSB) is the variance that we can explain; this variation is
due to the fact that we treated people differently (treatment conditions)
b) Within variance (SSW) is the variance that we cannot explain; we do not know
why people who were treated the same differed in their scores
What is directional hypothesis testing? - ANSWER When we use a directional
hypothesis, we are concerned with whether or not our observed differences are
in a pre-specified direction
What is nondirectional hypothesis testing? - ANSWER When we use a non-
directional hypothesis, we are concerned with whether or not our two samples,
or sample and population, differ significantly, regardless of the direction of the
difference
What is a 1-tailed statistical test? - ANSWER A test that computes the probability
of a sample mean being one or more points higher than the hypothesized mean
What type of hypothesis goes with a 1-tailed statistical test? - ANSWER We use a
directional hypothesis for a 1-tailed test
What is a 2-tailed statistical test? - ANSWER A test that computes the probability
of a sample mean differing by one or more points in either direction from the
hypothesized mean
What type of hypothesis goes with a 2-tailed statistical test? - ANSWER We use a
non-directional hypothesis for a 2-tailed test
What is type I error? - ANSWER Rejecting the null hypothesis when it is true
What is type II error? - ANSWER Not rejecting the null hypothesis when it is false
What is a sampling distribution? - ANSWER Hypothetical or theoretical
distributions of statistics (for instance, we can estimate the variability of the
difference between two means of a given sample size when the null hypothesis
is true - no difference in the population - this is the sampling distribution of the
difference between two means)
What are the 8 types of mean comparison procedures? - ANSWER 1. Linear
contrast
2. Bonferonni approach
3. Dunn-Sidak test
