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Test your basic knowledge |
DSST Intro To Statistics
Start Test
Study First
Subjects
:
dsst
,
statistics
Instructions:
Answer 50 questions in 15 minutes.
If you are not ready to take this test, you can
study here
.
Match each statement with the correct term.
Don't refresh. All questions and answers are randomly picked and ordered every time you load a test.
This is a study tool. The 3 wrong answers for each question are randomly chosen from answers to other questions. So, you might find at times the answers obvious, but you will see it re-enforces your understanding as you take the test each time.
1. Level of measurement- involves data that consist of names - labels and categories only. The data cannot be arranged in an ordering scheme (such as low to high). (Example) Nationalities of survey respondents
Frequency histogram
Sampling
Strata sampling
Nominal
2. An efficient method of graphing information using actual amounts: clusters - gaps - outliers are clearly identified.
s2
Self-selected sample
Stem and leaf plots
p value right tail
3. Sample variance
N
Distribution
s2
Outliers
4. Statistics
Numerical measurement describing some characteristic of a sample.
n
Graph
Sample
5. Parameter
Numerical measurement describing some characteristics of a population.
The 4 measures of center
Distribution
Symmetric Distribution
6. Population is organized into groups (i.e - neighborhoods/departments) - and sampling unit is selected by a simple random sample
Survey
Cluster sampling
Categorical Variable
Parameter
7. Has the same shape and horizontal scale as a histogram - but the vertical scale is marked with relative frequencies instead of actual frequencies
s
Relative frequency histogram
Discrete numerical data
q
8. Can be used to get an initial graphical view of data
Dot plots
Symmetric Distribution
Distribution
n
9. To find the range subtract the lowest value by the highest value.
Range
Statistic
Variable
Raw Data
10. Lowercase sigma; population standard deviaition
Designed experiment
s
Population
Cluster sampling
11. Data values that are either much larger or much smaller than the general body of data- they should be included in an analysis unless they are the result of human or other error
S x
Inferential Statistics
Outliers
Median
12. Using graphs and numerical summaries to describe variables in a data set and their relationship
Dot plots
The effect of extreme values on the measures of center
Center of Distribution
Exploratory data analysis
13. A survey that includes every item or individual of the population
Symmetric Distribution
Census
p
s
14. Sample standard deviation
Population Size
Stem-and-Leaf display
s
Census
15. Is a number that describes a characteristic of a population
Sample
Parameter
Graph
Population
16. Is the portion of the population that is selected for study
Dependent events
The 4 measures of center
Sample Size
Sample
17. Type of information - usually a property of characteristic of a person or thing that is measured or observed
Dependent events
Population Size
Variable
Dot plots
18. A flaw in the sampling procedure that makes it more likely that the sample will NOT be representative of population
S x
Parameter
Raw Data
Bias
19. Probability of event A
S x
P(A)
H0
Designed experiment
20. When the distribution of the data values greater than the center of the display - and the data values less than the center of the display are mirror images of each other
N
Symmetric Distribution
Outlier
Distribution
21. A method in which you randomly choose one number from 'l' to 'k' and continue to select the kth element
Pictograph
p value right tail
Simple random sample
Systematic sampling
22. For a left tailed test use normalcdf(-999 - ZTS)
Population
Categorical Variable
Independent events
p value left tail
23. Test use normalcdf(ZTS -999)
p value right tail
Survey
range
Statistic
24. (largest data value) - (smallest data value)
range
Population Size
Ordinal
Continuous Data
25. Collection of information from a sample
Sample
Center of Distribution
Survey
Representative Sample
26. Is denoted by 'N' - is the number of data values in the population
Census
Dependent events
Population Size
Dot plots
27. One extreme value can affect it dramatically.
Range
The effect of extreme values on the measures of center
Self-selected sample
28. Sample proportion
Simple Random Sample
Data Set
Categorical Variable
p
29. Range - standard deviation and variance.
Convenience sampling
Raw Data
Sample Variance
The 3 measures of variation
30. Middle value of a set of data values after they've been arranged in numerical order - 1. First arrange data values in numerical order 2. For odd # of data values - the median is the middle data value 3. For even # of data values - the median is the m
Ordinal
Median
H1
N
31. Create a sample by using data from population members that are readily available
Independent events
Categorical Variable
S x
Convenience sampling
32. To divide the population into 2 or more non-overlapping subsets called strata
s
Characteristic of a distribution
Data
Strata sampling
33. Is a collection of several data pertaining to one or more variables
Descriptive Statistics
Data Set
Sampling
Cluster sampling
34. A numerical quantity measuring some aspect of the population
Ordinal
Parameter
Convenience sampling
Frequency
35. A visual exploratory data analysis technique that shows the shape of a distribution - this kind of display uses the actual values of the variable to present the shape of the distribution of data values
Percentile
Stem-and-Leaf display
What symbol must always be found in H0
Parameter
36. Sample size or number of trials
n
Graph
Survey
S x
37. Represents categories - and is nonnumerical in nature
Categorical Variable
Stem-and-Leaf display
Dot plots
Strata sampling
38. Members of the population select themselves by volunteering
p value left tail
Population Size
Self-selected sample
Median
39. Information about individuals in a population
Sample Size
S
Data
Parameter
40. Determine the location of the middle value of all the data values
Center of Distribution
n
Designed experiment
Inferential Statistics
41. Occur when one of them affects the probability of the other.
Dependent events
The 4 measures of center
Frequency
Parameter
42. A method of experimentation in which you can control as many variables as possible in order to isolate the effects of a response variable
Self-selected sample
s2
Designed experiment
s2
43. Is the entire collection of all individuals or objects of interest
Self-selected sample
Sampling
Sample
Population
44. Double the answer from step 1 or step 2 (on whichever side your test statistics falls).
Sampling
Median
p value two tailed test
p
45. Sum of the values
Ratio
p
S x
p value right tail
46. Occur when one does not affect the probability of the occurrence of the other.
Independent events
Dependent events
Designed experiment
Outliers
47. A method of data collection where the researcher selects a sample from the population and measures the variable of interest
Nominal
Stem and leaf plots
S
Survey
48. Involves the procedures associated with the data collection process - the summarizing and interpretation of data - and the drawing of inferences or conclusions based on the analysis of the data
Statistics
Population
Ordinal
Numerical measurement describing some characteristic of a sample.
49. When the distribution of the data values tend to be concentrated toward one end of the display or tail of the distribution - while the data values in the other tail are spread out through extreme values resulting in a longer tail
Skewed Distribution
The effect of extreme values on the measures of center
Continuous Data
Population Size
50. Collection of information from the whole population
Census
Distribution
Observational study
Range