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AP Statistics Basics
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Terms in this set (65)
Statistics
Science of planning studies and experiments; obtaining data then organizing, presenting, analyzing and interpreting
Data
Collections of observations, such as measurements, genders, or survey responses
- Prepare
- Analyze
- Conclude
Key Elements in Statistical Thinking
- Context
- Source of Data
- Sampling Method
3 main key points of Prepare
Context
The circumstances or setting surrounding an event
Context
What do the data mean?
What is the goal of the study?
Source of Data
Are the data from a source with a special interest so that there is pressure to obtain results that are favorable to the source?
Sampling Method
Were the data collected in a way that is unbiased or biased?
Sound Sampling Method
absolutely essential for good results in a statistical study
Voluntary Response Samples
a type of survey that is generally bad to practice
- Internet Polls
- Mall-in Polls
- Telephone Call-in Polls
examples of Voluntary Response Samples
- Graph and Explore the Data
- Apply Statistical Methods
3 main key points of Analyze
Graph and Explore Data
...
Apply Statistical Methods
using technology to obtain results
Conclude
determining the significance of the study
- Statistical Significance
- Practical Significance
two main key points of Conclude
Statistical Significance
achieved in a study when we get the result that is very unlikely to occur by chance
Practical Significance
possible that a treatment or finding is effective by statistical standards, but common sense might suggest otherwise
Individuals
The objects described by a set of data
Variable
A characteristic or attribute that can assume different values
Data
values (measurements or observations) that the variables can assume
Population
the totality of all the elements or persons for which one has an interest at a particular time
N
Population is denoted by?
Sample
Subset of the population
n
Sample is denoted by?
Parameter
Numerical measurement describing some characteristic of a population
Statistics
numerical measurement describing some characteristic of a sample
- Descriptive Statistics
- Inferential Statistics
Areas of Statistics
Descriptive Statistics
Statistical methods used to describe and summarize sample data.
Descriptive Statistics
consists of the collection, organization, summarization, and presentation of data
Inferential Statistics
consists of methods that use sample results to help make decisions or predictions about a population
- Quantitative Data
- Categorial Data
Types of Data
Quantitative Data
also known as numerical data
Quantitative Data
consist of numbers representing counts or measurements
Categorial Data
also known as qualitative data
Categorial Data
consist of names or labels that are not numbers representing counts or measurements
- Discrete Variable
- Continuous Variable
Types of Variables
Discrete Variable
Assumes values that can be counted
Continuous Variable
can assume an infinite number of values in between any two specific values; obtained by measuring
- Nominal
- Ordinal
- Interval
- Ratio
Levels of Measurement
Nominal
data that consists of names, labels and categories only; cannot be arranged in order
Ordinal
Data that can be arranged in order but differences between values cant be determined or are meaningless
Interval
Data that can be ordered and the arithmetic difference is meaningful
Interval
data at this level doesn't have a natural zero starting point at which none of the quantity is present
Ratio
data that can be arranged in order, differences can be found and are meaningful; there is a natural zero starting point
Natural Zero Starting Point
what is the term used for zeroes that indicate that none of the quantity is present making differences and ratios meaningful
- Independent Variable
- Dependent Variable
Types of Variables in Research
Independent Variable
what the researcher chooses to study; can be manipulated
Dependent Variable
the measurable effect of the Independent Variable
- Moderator Variables
- Mediator Variables
- Extraneous Variables
Other types of variables in Research
Moderator Variables
secondary independent variable that was chosen to identify if it affects or modifies the relationship between the IV and the DV
Mediator Variables
attempts to explain the relationship between to other variables
Extraneous Variables
the external influences or effects of other variables
- Misleading Conclusions
- Reported Results
- Small Samples
- Loaded Questions
- Order of Questions
- Nonresponse
- Missing Data
- Precise Numbers
- Percentages
9 Potential Pitfalls in Data Analysis
Misleading Conclusions
a pitfall wherein conclusions are not always justifiable by statistical analysis
Reported Results
a pitfall wherein results are bias or in favor of one side
Small Samples
a pitfall wherein conclusions are based on small sample sizes
Loaded Questions
a pitfall wherein the questions are not worded carefully
Order of Questions
a pitfall wherein the sequencing of questions has an effect on the result
Nonresponse
a pitfall wherein someone refuses to respond
Missing Data
a pitfall that can be caused by dropping out of a survey or lying in a survey
Precise Numbers
a pitfall wherein the number that is given is exact, when it cannot actually be accurately determined
Percentages
a pitfall wherein the study cites misleading or unclear percentages
test-taking experience
identify the moderator variable:
Does anxiety affect test performance and, if so, does it depend on test-taking experience
socio-economic status
identify a mediarator variable:
Does anxiety affect test performance and, if so, does it depend on test-taking experience
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