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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. A numerical quantity measuring some aspect of the population
Simple random sample
Observational study
Parameter
Statistic (note there is no 's' at the end)
2. 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
s2
Stem-and-Leaf display
Representative Sample
H1
3. A method in which you randomly choose one number from 'l' to 'k' and continue to select the kth element
Sample
range
Sampling
Systematic sampling
4. Population variance
s2
Pictograph
Stem and leaf plots
s
5. Test use normalcdf(ZTS -999)
Census
Sample Size
p value right tail
P(A)
6. Occur when one does not affect the probability of the occurrence of the other.
Population
H0
Alpha (a)
Independent events
7. A method of data collection where the researcher selects a sample from the population and measures the variable of interest
Representative Sample
Population
Skewed Distribution
Survey
8. Members of the population select themselves by volunteering
Simple Random Sample
Outlier
Dependent events
Self-selected sample
9. Null hypothesis
Skewed Distribution
Statistics
H0
Inferential Statistics
10. 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
Data Set
Exploratory data analysis
Nominal
Range
11. Parameter
p
Self-selected sample
Outliers
Numerical measurement describing some characteristics of a population.
12. Is a sample containing similar characteristics of the population
Systematic sampling
Representative Sample
Distribution
x
13. 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
Raw Data
The effect of extreme values on the measures of center
Statistic
14. The important aspects of the data are called?
Characteristic of a distribution
Population Size
Data
Inferential Statistics
15. Using graphs and numerical summaries to describe variables in a data set and their relationship
s2
Convenience sampling
Population
Exploratory data analysis
16. 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
Outlier
Census
Sample
Skewed Distribution
17. Sample proportion
p
s2
Census
18. Is the entire collection of all individuals or objects of interest
The 4 measures of center
Statistic
Raw Data
Population
19. Mu; population mean
Simple Random Sample
Population Size
Observational study
20. One extreme value can affect it dramatically.
The effect of extreme values on the measures of center
Median
The 3 measures of variation
Population
21. 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
Representative Sample
Symmetric Distribution
Data
Simple Random Sample
22. A quantity calculated from data gathered from a sample- usually used to estimate a population parameter
Categorical Variable
Statistic
Stem-and-Leaf display
Sample
23. 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).
Bias
S x
Interval
Center of Distribution
24. _______________ are numerical values that can assume only a limited number of values
Relative frequency histogram
The 2 measures of relative standing
Systematic sampling
Discrete Data
25. A descriptive tool used to visually describe the characteristics and relationships of collections of data quickly and attractively
p value two tailed test
The 2 measures of relative standing
Nominal
Graph
26. Mean - mode - median and midrange.
Percentile
The 4 measures of center
Self-selected sample
Disjoint event
27. Is the process of selecting a portion - or sample - of the entire population
Sampling
Sample Size
Variable
Continuous Data
28. An efficient method of graphing information using actual amounts: clusters - gaps - outliers are clearly identified.
Frequency histogram
Stem and leaf plots
Dependent events
Systematic sampling
29. Is the process of using SAMPLE INFORMATION to draw inferences or conclusions about the POPULATION
Inferential Statistics
Frequency histogram
The 4 measures of center
Continuous Data
30. An individual data value which lies far (above or below) from most or all of the other data values within a distribution
What symbol must always be found in H0
Bias
range
Outlier
31. Sample size or number of trials
n
Frequency histogram
Numerical Variable
Dot plots
32. Always use a equal symbol
Sample Size
What symbol must always be found in H0
Sample
Relative frequency histogram
33. Collection of information from a sample
Survey
N
p
s
34. A method of data collection in which the objects of study are observed in their natural settings and the variables are recorded
Frequency histogram
Alpha (a)
Observational study
Strata sampling
35. Can be used to get an initial graphical view of data
Designed experiment
Center of Distribution
Distribution
Dot plots
36. Type of bar graph that shows frequency distributions
Median
Census
Discrete Data
Frequency histogram
37. 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
Categorical Variable
What symbol must always be found in H0
Random Sample or Probability Sample
Outliers
38. Uses numerical and or visual techniques to summarize or describe the data in a clear effective manner
Statistic (note there is no 's' at the end)
Population
Descriptive Statistics
Disjoint event
39. Population proportion
s
p
Sample
Sampling
40. A flaw in the sampling procedure that makes it more likely that the sample will NOT be representative of population
Bias
s
Population
n
41. (largest data value) - (smallest data value)
q
Observational study
Disjoint event
range
42. Probability of event A
Relative frequency histogram
s2
P(A)
p value right tail
43. Represents categories - and is nonnumerical in nature
Data
Categorical Variable
Relative frequency histogram
Graph
44. 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
Inferential Statistics
Percentile
Sample
Simple random sample
45. Population is organized into groups (i.e - neighborhoods/departments) - and sampling unit is selected by a simple random sample
Sample Size
Parameter
Cluster sampling
The 2 measures of relative standing
46. 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
p value left tail
q
Ordinal
Data
47. 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
Cluster sampling
The effect of extreme values on the measures of center
Random Sample or Probability Sample
48. The level of significance and the probability of a type I error (rejecting a true null hypothesis). The area in the tail or tails of a distribution (z - t - or ?2); in hypothesis testing you don't always have a two tailed distribution as in confidenc
Random Sample or Probability Sample
Outlier
n
Alpha (a)
49. A number that is used to describe a characteristic of a sample - such as a sample average - is called a __________.
Cluster sampling
Statistic (note there is no 's' at the end)
range
Statistic
50. Population size
Observational study
P(A)
N
Nominal