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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. Is a collection of several data pertaining to one or more variables
Dependent events
Data Set
Census
p
2. Type II error is measured
Designed experiment
Dot plots
Distribution
3. (largest data value) - (smallest data value)
range
p value two tailed test
Nominal
s2
4. Determine the location of the middle value of all the data values
Sample Variance
Bias
Census
Center of Distribution
5. Alternative hypothesis
H1
Statistic (note there is no 's' at the end)
Survey
s
6. Using graphs and numerical summaries to describe variables in a data set and their relationship
Exploratory data analysis
range
Interval
S x
7. To divide the population into 2 or more non-overlapping subsets called strata
Skewed Distribution
Strata sampling
Frequency
n
8. Is a number that describes a characteristic of a sample
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9. Sample variance
Raw Data
Representative Sample
Observational study
s2
10. Sample size or number of trials
Variable
Descriptive Statistics
Characteristic of a distribution
n
11. Lowercase sigma; population standard deviaition
Survey
q
Random Sample or Probability Sample
s
12. Population variance
Independent events
s2
Outliers
Discrete Data
13. An efficient method of graphing information using actual amounts: clusters - gaps - outliers are clearly identified.
Categorical Variable
Stem and leaf plots
The 2 measures of relative standing
14. Square the standard deviation and to find the population variance square of the population standard deviation
Variable
S
Sample Variance
15. 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
Population
Graph
Bias
16. Complement of p
Dependent events
Statistic
q
Exploratory data analysis
17. Sample proportion
Independent events
p
q
18. To calculate the percentile take the number of values less than x - divide by total number of values and times by 100.
Representative Sample
Range
The 2 measures of relative standing
Percentile
19. Represents categories - and is nonnumerical in nature
s
Independent events
Categorical Variable
Frequency histogram
20. Population is organized into groups (i.e - neighborhoods/departments) - and sampling unit is selected by a simple random sample
Representative Sample
Cluster sampling
Independent events
Characteristic of a distribution
21. 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
Random Sample or Probability Sample
s2
Survey
Distribution
22. Parameter
Statistic (note there is no 's' at the end)
Strata sampling
Numerical measurement describing some characteristics of a population.
Independent events
23. Is denoted by 'n' - is the number of data values in the sample
Statistic
Sample Size
Nominal
Cluster sampling
24. Is a sample containing similar characteristics of the population
Representative Sample
x
Parameter
Interval
25. Range - standard deviation and variance.
range
N
Observational study
The 3 measures of variation
26. Null hypothesis
Nominal
Population
H0
Cluster sampling
27. A method of data collection where the researcher selects a sample from the population and measures the variable of interest
Survey
Representative Sample
The 2 measures of relative standing
Simple Random Sample
28. Before they are arranged or analyzed - information or observations are called________.
Systematic sampling
Exploratory data analysis
Skewed Distribution
Raw Data
29. The important aspects of the data are called?
Characteristic of a distribution
Designed experiment
Systematic sampling
Distribution
30. Can be used to get an initial graphical view of data
Dot plots
Cluster sampling
Discrete Data
Representative Sample
31. 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
H1
Descriptive Statistics
Nominal
Dot plots
32. Type of information - usually a property of characteristic of a person or thing that is measured or observed
Skewed Distribution
Disjoint event
Variable
The 4 measures of center
33. 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
Sample
Numerical measurement describing some characteristic of a sample.
Outliers
34. A method of experimentation in which you can control as many variables as possible in order to isolate the effects of a response variable
Designed experiment
Disjoint event
Stem and leaf plots
The 4 measures of center
35. Probability of event A
P(A)
S
Frequency histogram
Cluster sampling
36. 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
Ordinal
Dot plots
Cluster sampling
37. Sum of the values
Statistic
S
Ratio
S x
38. Mu; population mean
The 3 measures of variation
Center of Distribution
Representative Sample
39. A method in which each combination of people has an equal chance of being selected- the sample is representative of the population and is independent
Numerical measurement describing some characteristics of a population.
Simple random sample
H0
S
40. The pattern of variation of data. The distribution may be described as symmetrical - positively skewed - or negatively skewed
Statistic (note there is no 's' at the end)
p value left tail
Distribution
Population
41. An individual data value which lies far (above or below) from most or all of the other data values within a distribution
Outlier
The effect of extreme values on the measures of center
Simple Random Sample
Categorical Variable
42. For a left tailed test use normalcdf(-999 - ZTS)
p value left tail
N
The 2 measures of relative standing
S
43. Double the answer from step 1 or step 2 (on whichever side your test statistics falls).
P(A)
p value two tailed test
Parameter
Discrete numerical data
44. A method in which you randomly choose one number from 'l' to 'k' and continue to select the kth element
S
Systematic sampling
N
Sample Variance
45. The number of times each data value occurs
Frequency
H1
Simple random sample
Sample
46. Disjoint events cannot overlap. They are mutually exclusive if they cannot occur at the same time.
Distribution
Disjoint event
Designed experiment
47. Uses numerical and or visual techniques to summarize or describe the data in a clear effective manner
Data Set
Statistic
Continuous Data
Descriptive Statistics
48. Information about individuals in a population
Statistic (note there is no 's' at the end)
Bias
Data
Ordinal
49. 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
Data
Convenience sampling
Symmetric Distribution
Statistic
50. 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
Survey
Statistics
Discrete Data
Stem-and-Leaf display