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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. Disjoint events cannot overlap. They are mutually exclusive if they cannot occur at the same time.
Survey
Discrete numerical data
Disjoint event
Statistics
2. Using graphs and numerical summaries to describe variables in a data set and their relationship
Exploratory data analysis
Sample
Stem-and-Leaf display
Survey
3. A quantity calculated from data gathered from a sample- usually used to estimate a population parameter
Statistic
Continuous Data
The 2 measures of relative standing
Center of Distribution
4. The pattern of variation of data. The distribution may be described as symmetrical - positively skewed - or negatively skewed
What symbol must always be found in H0
Dot plots
Statistics
Distribution
5. Probability of event A
Raw Data
P(A)
Bias
Stem and leaf plots
6. 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
Descriptive Statistics
Parameter
Symmetric Distribution
7. Is the process of using SAMPLE INFORMATION to draw inferences or conclusions about the POPULATION
Dependent events
Representative Sample
Descriptive Statistics
Inferential Statistics
8. A method in which you randomly choose one number from 'l' to 'k' and continue to select the kth element
Systematic sampling
Sample
Dependent events
P(A)
9. A subset of the population- it's important to choose a sample at random to avoid bias in the results
Sample Size
Sample
Frequency
Disjoint event
10. Represents categories - and is nonnumerical in nature
The 3 measures of variation
Data
Categorical Variable
Sample
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
Observational study
Statistic (note there is no 's' at the end)
Outliers
12. 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
N
Statistics
Variable
13. Complement of p
Systematic sampling
s
q
Strata sampling
14. Sum of the values
Outliers
Stem and leaf plots
S x
Nominal
15. A method of data collection in which the objects of study are observed in their natural settings and the variables are recorded
Observational study
p value two tailed test
Sample
Numerical Variable
16. Sample proportion
Sample Variance
Outlier
p value right tail
p
17. To calculate the percentile take the number of values less than x - divide by total number of values and times by 100.
Sample
Continuous Data
Percentile
Parameter
18. 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
Skewed Distribution
Interval
Relative frequency histogram
Alpha (a)
19. An individual data value which lies far (above or below) from most or all of the other data values within a distribution
Frequency histogram
Cluster sampling
Outlier
Ordinal
20. 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
Graph
Relative frequency histogram
Simple random sample
Raw Data
21. Alternative hypothesis
H1
Statistics
Observational study
Simple Random Sample
22. Members of the population select themselves by volunteering
Self-selected sample
p value two tailed test
H0
Statistics
23. 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
Frequency histogram
p
The 3 measures of variation
24. _______________ are numerical values that can assume only a limited number of values
Graph
Discrete Data
q
Sample
25. The number of times each data value occurs
Strata sampling
Frequency
p
26. Null hypothesis
Simple random sample
p value right tail
Inferential Statistics
H0
27. Sample variance
Convenience sampling
p
s2
Random Sample or Probability Sample
28. 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
Discrete numerical data
Simple Random Sample
Percentile
Interval
29. A survey that includes every item or individual of the population
Census
s2
Population
Ratio
30. A method of data collection where the researcher selects a sample from the population and measures the variable of interest
Frequency histogram
Relative frequency histogram
Sampling
Survey
31. Population variance
Outliers
Survey
p
s2
32. Capital sigma; summation
Symmetric Distribution
S
Raw Data
range
33. Population size
Representative Sample
N
The 4 measures of center
Variable
34. Uses numerical and or visual techniques to summarize or describe the data in a clear effective manner
Parameter
Descriptive Statistics
The 4 measures of center
Simple random sample
35. 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
Sample Variance
Nominal
Population
Distribution
36. An efficient method of graphing information using actual amounts: clusters - gaps - outliers are clearly identified.
x
Stem and leaf plots
S x
Alpha (a)
37. Has the same shape and horizontal scale as a histogram - but the vertical scale is marked with relative frequencies instead of actual frequencies
Data
Simple random sample
p value left tail
Relative frequency histogram
38. Statistics
Strata sampling
Numerical measurement describing some characteristic of a sample.
Parameter
Graph
39. The important aspects of the data are called?
Outlier
s2
Characteristic of a distribution
Designed experiment
40. 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
Descriptive Statistics
Interval
Symmetric Distribution
41. Is a number that describes a characteristic of a population
Survey
Frequency histogram
Parameter
Census
42. Type II error is measured
Statistic
Sample
Outliers
43. Create a sample by using data from population members that are readily available
Systematic sampling
Nominal
Convenience sampling
s2
44. The variable value can be represented as isolated points on a number line
Discrete numerical data
Parameter
Statistic
Statistic
45. 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
Relative frequency histogram
Self-selected sample
Ratio
Simple random sample
46. Standard scores and percentile
Convenience sampling
Ratio
The 2 measures of relative standing
Self-selected sample
47. Determine the location of the middle value of all the data values
Self-selected sample
Center of Distribution
Disjoint event
Raw Data
48. Can be used to get an initial graphical view of data
Dependent events
p value right tail
p
Dot plots
49. _______________ are numerical measurements that can assume any value between two numbers
Continuous Data
range
Cluster sampling
50. A method of experimentation in which you can control as many variables as possible in order to isolate the effects of a response variable
Exploratory data analysis
Designed experiment
p
Discrete numerical data