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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. 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
s2
Designed experiment
Alpha (a)
2. 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
Designed experiment
Symmetric Distribution
s2
Nominal
3. Is a collection of several data pertaining to one or more variables
Population Size
Interval
Data Set
Simple random sample
4. Occur when one of them affects the probability of the other.
Survey
Numerical measurement describing some characteristics of a population.
Sample
Dependent events
5. Test use normalcdf(ZTS -999)
p value right tail
Self-selected sample
q
Inferential Statistics
6. Is the process of using SAMPLE INFORMATION to draw inferences or conclusions about the POPULATION
P(A)
Categorical Variable
Numerical measurement describing some characteristics of a population.
Inferential Statistics
7. Create a sample by using data from population members that are readily available
Convenience sampling
Data Set
Sample Size
Observational study
8. Represents categories - and is nonnumerical in nature
Population
Parameter
Range
Categorical Variable
9. An efficient method of graphing information using actual amounts: clusters - gaps - outliers are clearly identified.
Center of Distribution
Bias
Frequency histogram
Stem and leaf plots
10. Is the entire collection of all individuals or objects of interest
Population
P(A)
Parameter
Graph
11. Null hypothesis
Pictograph
S x
H0
Distribution
12. Standard scores and percentile
Bias
P(A)
Alpha (a)
The 2 measures of relative standing
13. The number of times each data value occurs
Frequency histogram
Simple random sample
Parameter
Frequency
14. 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
Skewed Distribution
Population Size
Outliers
Numerical Variable
15. Disjoint events cannot overlap. They are mutually exclusive if they cannot occur at the same time.
Bias
Disjoint event
Strata sampling
Median
16. An individual data value which lies far (above or below) from most or all of the other data values within a distribution
Data
Distribution
Outlier
Disjoint event
17. Mean - mode - median and midrange.
Cluster sampling
The 4 measures of center
Median
Parameter
18. Variable where the value is a number that results from a measurement process - also called numerical data
Numerical Variable
Distribution
Stem-and-Leaf display
Outlier
19. Can be used to get an initial graphical view of data
x
Symmetric Distribution
Dot plots
Bias
20. Level of measurement- Is the interval level modified to include the inherent zero starting point (where zero indicates that none of the quantity is present). For values at this level - differences and ratios are both meaningful. (Example) Ages of sur
Bias
Descriptive Statistics
Ratio
Sample Variance
21. For a left tailed test use normalcdf(-999 - ZTS)
Raw Data
p value left tail
p
range
22. 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
Pictograph
Random Sample or Probability Sample
S x
Outliers
23. Sample standard deviation
Sample
Disjoint event
s
Census
24. Is a sample containing similar characteristics of the population
Representative Sample
Relative frequency histogram
Cluster sampling
Percentile
25. Is a number that describes a characteristic of a sample
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26. To calculate the percentile take the number of values less than x - divide by total number of values and times by 100.
Percentile
Observational study
Nominal
Categorical Variable
27. Sample mean
P(A)
Data Set
x
Percentile
28. The variable value can be represented as isolated points on a number line
N
Symmetric Distribution
Discrete numerical data
H0
29. A descriptive tool used to visually describe the characteristics and relationships of collections of data quickly and attractively
s2
The effect of extreme values on the measures of center
Designed experiment
Graph
30. Using graphs and numerical summaries to describe variables in a data set and their relationship
Census
The 4 measures of center
Exploratory data analysis
Pictograph
31. Collection of information from a sample
N
Outlier
Survey
p value two tailed test
32. (largest data value) - (smallest data value)
range
Designed experiment
Statistic
x
33. 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
Representative Sample
Center of Distribution
Percentile
Nominal
34. The important aspects of the data are called?
Convenience sampling
Characteristic of a distribution
Categorical Variable
Frequency
35. To find the range subtract the lowest value by the highest value.
p value two tailed test
Range
Inferential Statistics
Outlier
36. 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
Ordinal
Convenience sampling
Numerical measurement describing some characteristics of a population.
37. A method of data collection in which the objects of study are observed in their natural settings and the variables are recorded
Parameter
p value right tail
Observational study
Continuous Data
38. Lowercase sigma; population standard deviaition
p value right tail
s
Convenience sampling
Bias
39. Is a number that describes a characteristic of a population
Sample Variance
Descriptive Statistics
Representative Sample
Parameter
40. Is a sample that has the pertinent characteristics of the population in the same proportion - as they are included in that population
Representative Sample
p
Distribution
Convenience sampling
41. A method in which you randomly choose one number from 'l' to 'k' and continue to select the kth element
Systematic sampling
Representative Sample
Dependent events
Population Size
42. Probability of event A
Designed experiment
p
P(A)
43. Members of the population select themselves by volunteering
Self-selected sample
Disjoint event
Distribution
Convenience sampling
44. Parameter
Simple random sample
Statistic
p
Numerical measurement describing some characteristics of a population.
45. 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
Bias
q
Frequency histogram
Ordinal
46. A flaw in the sampling procedure that makes it more likely that the sample will NOT be representative of population
Bias
Numerical measurement describing some characteristics of a population.
Statistics
Stem and leaf plots
47. One extreme value can affect it dramatically.
Strata sampling
Exploratory data analysis
The effect of extreme values on the measures of center
Interval
48. Type of information - usually a property of characteristic of a person or thing that is measured or observed
Self-selected sample
Numerical Variable
Variable
Center of Distribution
49. Sum of the values
The 4 measures of center
S x
Distribution
Representative Sample
50. 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
Representative Sample
range
Simple Random Sample
Categorical Variable