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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. Statistics
x
Dependent events
s2
Numerical measurement describing some characteristic of a sample.
2. Is the portion of the population that is selected for study
Self-selected sample
H1
Sample
Distribution
3. 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
Stem-and-Leaf display
Frequency histogram
The 2 measures of relative standing
Distribution
4. Graph involving pictures of objects in which the size of the object in which the size of the object in the picture represents the relative size of the quantity being represented by the object.
Pictograph
Representative Sample
Disjoint event
H0
5. Sample variance
Random Sample or Probability Sample
s2
Frequency
Discrete Data
6. Is the entire collection of all individuals or objects of interest
Population Size
Population
Representative Sample
Center of Distribution
7. A method of data collection in which the objects of study are observed in their natural settings and the variables are recorded
q
Observational study
Interval
Systematic sampling
8. Information about individuals in a population
Outliers
Data
Convenience sampling
Numerical measurement describing some characteristics of a population.
9. Range - standard deviation and variance.
Simple random sample
The 3 measures of variation
H1
Categorical Variable
10. Can be used to get an initial graphical view of data
Simple Random Sample
Simple random sample
Relative frequency histogram
Dot plots
11. Standard scores and percentile
The 2 measures of relative standing
Exploratory data analysis
Population
Data
12. Represents categories - and is nonnumerical in nature
p value two tailed test
Designed experiment
Categorical Variable
Statistic
13. Test use normalcdf(ZTS -999)
Stem-and-Leaf display
Nominal
Frequency histogram
p value right tail
14. Is denoted by 'n' - is the number of data values in the sample
Numerical Variable
Stem-and-Leaf display
Pictograph
Sample Size
15. For a left tailed test use normalcdf(-999 - ZTS)
Designed experiment
Representative Sample
p value left tail
Simple random sample
16. Level of measurement- Involves data that may be arranged in some order - but differences between data values either cannot be determined or are meaningless. (Example) Questions on a survey are scored with integers 1 thru 5 with 1 representing strong
Descriptive Statistics
Symmetric Distribution
Designed experiment
Ordinal
17. A descriptive tool used to visually describe the characteristics and relationships of collections of data quickly and attractively
Categorical Variable
Graph
Median
Survey
18. A method of data collection where the researcher selects a sample from the population and measures the variable of interest
Pictograph
Survey
Discrete numerical data
Characteristic of a distribution
19. Double the answer from step 1 or step 2 (on whichever side your test statistics falls).
p value two tailed test
Outliers
S
20. Type II error is measured
Strata sampling
p value two tailed test
Distribution
21. Determine the location of the middle value of all the data values
Alpha (a)
p
Sample Size
Center of Distribution
22. Is a collection of several data pertaining to one or more variables
Percentile
Data Set
Observational study
Numerical measurement describing some characteristic of a sample.
23. Is the process of using SAMPLE INFORMATION to draw inferences or conclusions about the POPULATION
Inferential Statistics
Ordinal
Median
s2
24. Probability of event A
Distribution
Survey
P(A)
Strata sampling
25. Parameter
Graph
Sample Size
Data Set
Numerical measurement describing some characteristics of a population.
26. Capital sigma; summation
Inferential Statistics
The 3 measures of variation
Survey
S
27. Is a sample of data values selected from a population in such a way that every sample of size 'n' has an equal probability of being selected and every data value of the population has the same chance of being selected for the sample
Simple Random Sample
s
P(A)
n
28. (largest data value) - (smallest data value)
p value left tail
Data
range
Nominal
29. Population variance
Designed experiment
s2
Outlier
30. A quantity calculated from data gathered from a sample- usually used to estimate a population parameter
Statistic
p value two tailed test
p
Designed experiment
31. Sample proportion
s2
Sampling
p
Parameter
32. Using graphs and numerical summaries to describe variables in a data set and their relationship
Skewed Distribution
The 2 measures of relative standing
Exploratory data analysis
Independent events
33. Square the standard deviation and to find the population variance square of the population standard deviation
Parameter
Dot plots
Random Sample or Probability Sample
Sample Variance
34. Lowercase sigma; population standard deviaition
p
s
The 3 measures of variation
Simple Random Sample
35. Is the process of selecting a portion - or sample - of the entire population
Skewed Distribution
Sampling
Categorical Variable
36. Is a number that describes a characteristic of a sample
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37. To find the range subtract the lowest value by the highest value.
s
Range
Self-selected sample
Random Sample or Probability Sample
38. A number that is used to describe a characteristic of a sample - such as a sample average - is called a __________.
Data
Statistic
Nominal
Center of Distribution
39. Type of bar graph that shows frequency distributions
H1
Sample Size
Frequency histogram
Representative Sample
40. A method of experimentation in which you can control as many variables as possible in order to isolate the effects of a response variable
Continuous Data
Designed experiment
Numerical measurement describing some characteristic of a sample.
Alpha (a)
41. A sample which is selected in such a manner - that each data value of the population has a non-zero probability of being selected for the sample
Census
Numerical Variable
Random Sample or Probability Sample
Variable
42. Alternative hypothesis
H0
H1
Relative frequency histogram
Stem-and-Leaf display
43. Mu; population mean
n
Inferential Statistics
Alpha (a)
44. Level of measurement- Is like the ordinal level - with the additional property that we can determine meaningful amounts of differences between data. However - there is no inherent (natural) zero starting point (where none of the quantity is present).
Systematic sampling
Interval
Observational study
Discrete Data
45. 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
Dot plots
Sample Size
Nominal
Graph
46. 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
Self-selected sample
Cluster sampling
Statistics
Convenience sampling
47. A flaw in the sampling procedure that makes it more likely that the sample will NOT be representative of population
s
Bias
x
48. A numerical quantity measuring some aspect of the population
Dot plots
n
H1
Parameter
49. To calculate the percentile take the number of values less than x - divide by total number of values and times by 100.
Skewed Distribution
Percentile
Stem and leaf plots
Data
50. Sample standard deviation
Census
Random Sample or Probability Sample
range
s