PSY:2811 (Research Methods and Data
Analysis in Psych I) Exam #2
What are the two broad classes of statistical methods?
...ANSWER...1. Descriptive
2. Inferential
Descriptive Statistics
...ANSWER...A set of statistics used to organize and summarize the properties of a set
of data
What is the purpose of descriptive statistics?
...ANSWER...1. Organize data
2. Screen data for issues
3. Summarize main features of the data
4. Visualize data with graphs
5. Describe data from the sample
What questions can be answered using descriptive statistics?
...ANSWER...1. What is the most common value or range of values for a variable?
2. What is the shape of the distribution?
3. How much spread, or variability, is there in values for a variable?
4. Which variables are related to each other?
Inferential Statistics
,...ANSWER...A set of techniques that uses the laws of chance and probability to help
researchers make decisions about what their data mean and what inferences they can
make from them
What is the purpose of inferential statistics?
...ANSWER...Use data from a sample to infer general patterns and conclusions about a
population
Population ...ANSWER...The total collection of things (people, trees, animals, etc) that
we seek information about
Population Parameter ...ANSWER...Any summary number that describes characteristics
of the entire population; a fixed quantity or statistical measure that is used as the value
of a variable in some general distribution or frequency function to make it descriptive of
that population
Sample ...ANSWER...A representative collection of the things drawn from the
population; a subset of the population
Sample (Descriptive) Statistic ...ANSWER...Any summary number that describes the
sample
Sample Statistic Vs. Population Parameter ...ANSWER...Sample Statistic:
n → Number of cases/scores
X̅ → Mean
s² → Variance
s → Standard Deviation
Population Parameter:
N → Number of cases/scores
µ → Mean
σ² → Variance
σ → Standard Deviation
What is the difference between a population parameter and a sample
statistic? ...ANSWER...1. A population parameter is frequently impractical or impossible
to find for large populations while a sample statistic is often easier to find and provides a
reasonable approximation to the population parameter
What are the population, parameter of interest, sample, descriptive statistic, and
inference for the question, how much do apples from Wilson's orchard
weigh? ...ANSWER...Population: All the apples at Wilson's apple orchard
Parameter of Interest: µ (mu) estimated average weight
,Sample: A set of 100 apples picked from the trees
Descriptive Statistic: The actual average weight of your sample of apples
Inference: Sample mean = 149 g → population mean = about 149 g
Why can population parameters from samples only be estimated or
inferred? ...ANSWER...1. Samples differ from each other and may not be able to
represent the whole population, which can lead to error
2. A sampling error is the difference between the sample statistic and the population
parameter
Sampling Error ...ANSWER...An error that occurs when a sample does not represent
the target population
What are the population, parameter of interest, sample, and descriptive statistic for the
question, how far can a typical University of Iowa undergraduate throw a
football? ...ANSWER...Population: All of the undergraduate students at the University of
Iowa
Parameter of Interest: µ average distance thrown
Sample: A set of 30 students sampled from campus
Descriptive Statistic: The actual average of throwing distance thrown of those in your
sample
What are the population, parameter of interest, sample, and descriptive statistic for the
question, is there a relationship between social media use and anxiety in
teenagers? ...ANSWER...Population: All of the teenagers in the world
Parameter of Interest: ρ (rho) correlation between social media use and anxiety
Sample: A set of 200 teenagers sampled from Iowa City
Descriptive Statistic: r correlation between social media use and anxiety computed from
your sample
Inference ...ANSWER...The process of drawing conclusions about population
parameters based on a sample taken from the population
Histogram ...ANSWER...A data visualization technique showing how many of the cases
in a batch of data scored each possible value (the range of values/distribution) on the
variable
, What can be determined from a histogram? ...ANSWER...1. Shape of distribution
2. Most common values for each variable
3. The variability of values for each variable
Confidence Interval (CI) ...ANSWER...A given range indicated by a lower and upper
value that is designed to capture the population value for some point estimate
(percentage, difference, or correlation); a high proportion of CIs will capture the true
proportion value
What is the purpose of confidence intervals? ...ANSWER...1. Helps express a
population estimate as a range of best bet
2. Provides a probable range of values that, with a known degree of certainty, includes
an unknown population characteristic, such as a population mean
How can you calculate confidence intervals? ...ANSWER...CI = X̅ ± z(s/√n)
X̅ = Sample mean
z = Confidence level value
s = Sample standard deviation
n = Sample size
What would the range for a 95% confidence interval be if the sample average is
149? ...ANSWER...[147, 151]
The ___ of confidence intervals gives a probable window for the population
parameter ...ANSWER...Width
What does the width of the confidence interval measure? ...ANSWER...1. The variation
within the population of interest (similar population vs. different population)
2. The size of the sample (small sample vs. large sample)
3. Sample size is an important factor in determining confidence interval
What is the relation between population variation and the width of the confidence
interval? ...ANSWER...1. A population with low variation leads to similar samples with
low variation → narrow CI
2. A population with lots of variation leads to varied samples with lots of variation →
wide CI
3. Generally speaking, the narrower the CI, the better
Analysis in Psych I) Exam #2
What are the two broad classes of statistical methods?
...ANSWER...1. Descriptive
2. Inferential
Descriptive Statistics
...ANSWER...A set of statistics used to organize and summarize the properties of a set
of data
What is the purpose of descriptive statistics?
...ANSWER...1. Organize data
2. Screen data for issues
3. Summarize main features of the data
4. Visualize data with graphs
5. Describe data from the sample
What questions can be answered using descriptive statistics?
...ANSWER...1. What is the most common value or range of values for a variable?
2. What is the shape of the distribution?
3. How much spread, or variability, is there in values for a variable?
4. Which variables are related to each other?
Inferential Statistics
,...ANSWER...A set of techniques that uses the laws of chance and probability to help
researchers make decisions about what their data mean and what inferences they can
make from them
What is the purpose of inferential statistics?
...ANSWER...Use data from a sample to infer general patterns and conclusions about a
population
Population ...ANSWER...The total collection of things (people, trees, animals, etc) that
we seek information about
Population Parameter ...ANSWER...Any summary number that describes characteristics
of the entire population; a fixed quantity or statistical measure that is used as the value
of a variable in some general distribution or frequency function to make it descriptive of
that population
Sample ...ANSWER...A representative collection of the things drawn from the
population; a subset of the population
Sample (Descriptive) Statistic ...ANSWER...Any summary number that describes the
sample
Sample Statistic Vs. Population Parameter ...ANSWER...Sample Statistic:
n → Number of cases/scores
X̅ → Mean
s² → Variance
s → Standard Deviation
Population Parameter:
N → Number of cases/scores
µ → Mean
σ² → Variance
σ → Standard Deviation
What is the difference between a population parameter and a sample
statistic? ...ANSWER...1. A population parameter is frequently impractical or impossible
to find for large populations while a sample statistic is often easier to find and provides a
reasonable approximation to the population parameter
What are the population, parameter of interest, sample, descriptive statistic, and
inference for the question, how much do apples from Wilson's orchard
weigh? ...ANSWER...Population: All the apples at Wilson's apple orchard
Parameter of Interest: µ (mu) estimated average weight
,Sample: A set of 100 apples picked from the trees
Descriptive Statistic: The actual average weight of your sample of apples
Inference: Sample mean = 149 g → population mean = about 149 g
Why can population parameters from samples only be estimated or
inferred? ...ANSWER...1. Samples differ from each other and may not be able to
represent the whole population, which can lead to error
2. A sampling error is the difference between the sample statistic and the population
parameter
Sampling Error ...ANSWER...An error that occurs when a sample does not represent
the target population
What are the population, parameter of interest, sample, and descriptive statistic for the
question, how far can a typical University of Iowa undergraduate throw a
football? ...ANSWER...Population: All of the undergraduate students at the University of
Iowa
Parameter of Interest: µ average distance thrown
Sample: A set of 30 students sampled from campus
Descriptive Statistic: The actual average of throwing distance thrown of those in your
sample
What are the population, parameter of interest, sample, and descriptive statistic for the
question, is there a relationship between social media use and anxiety in
teenagers? ...ANSWER...Population: All of the teenagers in the world
Parameter of Interest: ρ (rho) correlation between social media use and anxiety
Sample: A set of 200 teenagers sampled from Iowa City
Descriptive Statistic: r correlation between social media use and anxiety computed from
your sample
Inference ...ANSWER...The process of drawing conclusions about population
parameters based on a sample taken from the population
Histogram ...ANSWER...A data visualization technique showing how many of the cases
in a batch of data scored each possible value (the range of values/distribution) on the
variable
, What can be determined from a histogram? ...ANSWER...1. Shape of distribution
2. Most common values for each variable
3. The variability of values for each variable
Confidence Interval (CI) ...ANSWER...A given range indicated by a lower and upper
value that is designed to capture the population value for some point estimate
(percentage, difference, or correlation); a high proportion of CIs will capture the true
proportion value
What is the purpose of confidence intervals? ...ANSWER...1. Helps express a
population estimate as a range of best bet
2. Provides a probable range of values that, with a known degree of certainty, includes
an unknown population characteristic, such as a population mean
How can you calculate confidence intervals? ...ANSWER...CI = X̅ ± z(s/√n)
X̅ = Sample mean
z = Confidence level value
s = Sample standard deviation
n = Sample size
What would the range for a 95% confidence interval be if the sample average is
149? ...ANSWER...[147, 151]
The ___ of confidence intervals gives a probable window for the population
parameter ...ANSWER...Width
What does the width of the confidence interval measure? ...ANSWER...1. The variation
within the population of interest (similar population vs. different population)
2. The size of the sample (small sample vs. large sample)
3. Sample size is an important factor in determining confidence interval
What is the relation between population variation and the width of the confidence
interval? ...ANSWER...1. A population with low variation leads to similar samples with
low variation → narrow CI
2. A population with lots of variation leads to varied samples with lots of variation →
wide CI
3. Generally speaking, the narrower the CI, the better
