Title: Exam 1A Chs 1 - 5
Course: PSYC 301 Statistical Methods in Psychol > Section: First Part of Course

Q: Fundamentally, what does Simpson's Paradox show us?
- Simple and surface-level analysis can mask important truths.
- Statistical analysis should not be trusted.
- Internal validity is difficult to create in a study.
- Use of computer analysis eases interpretation of statistics.
A: Simple and surface-level analysis can mask important truths.

Q: Why is statistics such a commonly used tool in psychological research?
- We measure things that have high variability and statistics handles that problem.
- It is easy to create a preferable 'story of the data'.
- The logic of experiments requires statistical analysis.
- Because it is the tool used in the past, it must be used in the future to be able to compare findings.
A: We measure things that have high variability and statistics handles that problem.

Q: Select from below all the responses that are correct.

Select the characteristics of ratio scaled data.
- naming of values
- ranking
- zero means a quantity that is 'nothing'
- distances between scores have equal meaning
A: naming of values; ranking; zero means a quantity that is 'nothing'; distances between scores have equal meaning

Q: What is meant by the research term, operationalization?
- Turning a concept for a variable into some specific method of measuring it.
- The procedural steps of performing the research project.
- The inherent vagueness of meaning for a variable.
- A framework for understanding a psychological principle.
A: Turning a concept for a variable into some specific method of measuring it.

Q: According to the book, a(n) __________is the same as what we learned in 201 as the independent variable and a(n) _________ is the same as what we learned in 201 as the dependent variable.
- predictor; outcome
- outcome; predictor
- extraneous; confounding
- confounding; extraneous
A: predictor; outcome

Q: Which of the below describes test-retest reliability?
- The same persons are measured on two different occasions, then their scores are compared.
- The same persons are measured using two different versions, which are then compared.
- Two observers of the persons give their independent measures, which are then compared.
- Individual item scores are compared to the total score of the scale.
A: The same persons are measured on two different occasions, then their scores are compared.

Q: Select from below all the responses that are correct.

Select the characteristics of ordinal scaled data.
- naming of values
- ranking
- zero means a quantity that is 'nothing'
- distances between scores indicate equal quantity differences.
A: naming of values; ranking

Q: Why is it better to use computer software than to work by hand. Select all that are correct.
- Computers calculate much faster
- Computers calculate more accurately
- Computers replaced people who did the job
- Computers aid in interpretation of results
A: Computers calculate much faster; Computers calculate more accurately

Q: What type of validity describes the degree to which our measurement process actually is measuring what we intend for it to measure?
- Construct Validity
- Internal Validity
- External Validity
- Mean Validity
A: Construct Validity

Q: Which of the following are true of jamovi. Select all that are correct.
- Free
- Can be installed on the vast majority of laptop or desktop computers
- Based on an excellent statistical program called R
- Provides output that changes instantly
A: Free; Can be installed on the vast majority of laptop or desktop computers; Based on an excellent statistical program called R; Provides output that changes instantly

Q: What is meant by the term 'descriptive statistics'?
- calculations that summarize data in a simple and compact way
- methods that result in descriptive sentences and paragraphs about the data
- calculation methods that are simple to apply to the data
A: calculations that summarize data in a simple and compact way

Q: What is the key thing we can do to ensure that we don't have a threat to internal validity due to differences between the groups in our conditions?
- Random Assignment
- Random Selection
- Confound Assignment
- Outcome Selection
A: Random Assignment

Q: When your data has one value that is very much different from the remainder of the distribution of data, what is the best measure of central tendency?
- Median
- Mean
- Mode
A: Median

Q: Kurtosis refers to what characteristics of a distribution of data?
- how flat the distribution is compared to a normal curve
- the suitability of the measuring scale for use of certain statistical calculations
- the degree of use of the entire range of possible values for a measuring system
A: how flat the distribution is compared to a normal curve

Q: What concept are we trying to capture with measures of variability?
- the degree of spread of the data distribution
- the centroid of the distribution
- if the mean can be relied upon
A: the degree of spread of the data distribution

Q: Which of the terms below accurately applies to the distribution below?
- positive skew
- negative skew
- no skew
A: positive skew

Q: What is the difference between standard deviation and variance?
- the standard deviation is the square root of variance
- the standard deviation is more precise than the variance
- the standard deviation takes into account the mean while the variance takes into account the median
A: the standard deviation is the square root of variance

Q: Imagine a data set for which I've already calculated a mean of 10.00. Imagine further that I add one more value to the data set which happens to have a value of 10.00. Will a new mean calculated from the revised data set be larger, smaller, or the same as the previous mean of 10.00?
- the same
- larger
- smaller
A: the same

Q: Imagine a data set for which I've already calculated a mean of 10.00 and a standard deviation of 3.00. Imagine further that I add one more value to the data set which happens to have a value of 10.00. Will a new standard deviation calculated from the revised data set be larger, smaller, or the same as the previous standard deviation of 3.00?
- smaller
- the same
- larger
A: smaller

Q: Which of the below are the goals for graphical presentation of data? Select all that are correct.
- Clear communication of data
- Accurate depiction of data
- Helping the data to 'tell its story'
- Artistically balanced presentation
A: Clear communication of data; Accurate depiction of data; Helping the data to 'tell its story'

Q: Which of the following are true of bar graphs and histograms, individually and in comparison to each other? Select all that are correct.
- Histograms are for ordinal and nominal data
- Bar Graphs are for ratio and interval data
- Bar graphs have space between the bars
- Histograms have no space between the bars
- Height of bars represents the density or frequency of observations
- The width of bars in bar graphs represents the modal response
A: Bar graphs have space between the bars; Histograms have no space between the bars; Height of bars represents the density or frequency of observations

Q: Florence Nightengale's Coxcomb has a similar deceptive characteristic as pie charts, the size of the 'wedge' is proportional to the data in only one dimension leading to the area increasing by a kind of 'spread' of the data. Which of the below explains why this is a deceptive characteristic?
- The increase in data size is perceived as a mass rather than as a comparable line
- The wedges are difficult to compare one to the next
- Readability is deceptively enhanced by the text written in the expanded open space, implying greater meaning
A: The increase in data size is perceived as a mass rather than as a comparable line

Q: John Snow's use of a _______ was convincing to the local council that a particular pump was responsible for the spread of disease.
- map of London streets showing each death and pump locations, an early form of 'heat map',
- bar graphs showing the number of deaths within 1/2 mile of each pump
- use of a coxcomb graph to demonstrate the increase in deaths near one particular pump
A: map of London streets showing each death and pump locations, an early form of 'heat map',

Q: Why might the mode be a very bad way to measure central tendency?
- if the data is very skewed, the mode is likely to be one of the smallest or largest values and not close to the middle
- the mode is very sensitive to outliers in the data, so with that kind of data, beware
- the mode is particularly sensitive to experimenter bias
A: if the data is very skewed, the mode is likely to be one of the smallest or largest values and not close to the middle