MATH 110 -Statistics (Ch 1)
Data
collections of observations
ex. measurements, genders, survey responses, etc
Statistics
The science of planning studies & experiments, obtaining data then organizing, summarizing,
presenting, analyzing, interpreting, & drawing conclusions based on that data.
Making inferences/generalizations about a population
Population
complete collection of all individuals to be studied
ex. measurements, scores, people
Census
collection of data from every member of the population, collecting data from all individuals
Sample
a subcollection of members selected from a population
data mush be collected through random selection, must be representative of the population
Main idea of statistics:
concept of data, source of data, sampling method, drawing conclusions, coming up w practical
implications. Learning to make sense of the data provided
context
a description of what the values represent, there they came from & why they were collected. It
is specific descriptions for the data provided
Always consider the context of data, ...
it affects the statistical analysis that should be used
Some sources of data are..
objective or biased & is not always reliable
The sampling method you choose can greatly influence..
the validity of your conclusions
, Samples may have..
bias & are not always valid
voluntary response sample (aka self-selected sample)
where respondents decide whether or not to be included in the survey/sample
ex. internet surveys, surveys by mail, surveys by phone
practical implications
drawing a sensible conclusion from your results
statistical significance:
statistically there's a difference, the thing is you may have insignificant results
Practical significance..
focuses more on practicality & common sense, something more realistic
statistical thinking
the ability to see the big picture & consider relevant factors such as context, source of data &
sampling to method to form conclusions & identify practical implications. Involved critical
thinking & the ability to make sense of results
Parameter (type of data)
a numerical measurement describing some characteristic of a population
Statistic (type of data)
a numerical measurement describing some characteristic of a sample
Quantitative data
numerical data, based on #'s, representing counts or measurements
ex. dollars, hours, feet, meters, minutes, seconds
Categorical/Qualitative data
data that is not numerical & represents counts or measures
ex. data consisting of names, attributes, etc
Quantitative data types:
discrete data & continuous data
discrete data
Data
collections of observations
ex. measurements, genders, survey responses, etc
Statistics
The science of planning studies & experiments, obtaining data then organizing, summarizing,
presenting, analyzing, interpreting, & drawing conclusions based on that data.
Making inferences/generalizations about a population
Population
complete collection of all individuals to be studied
ex. measurements, scores, people
Census
collection of data from every member of the population, collecting data from all individuals
Sample
a subcollection of members selected from a population
data mush be collected through random selection, must be representative of the population
Main idea of statistics:
concept of data, source of data, sampling method, drawing conclusions, coming up w practical
implications. Learning to make sense of the data provided
context
a description of what the values represent, there they came from & why they were collected. It
is specific descriptions for the data provided
Always consider the context of data, ...
it affects the statistical analysis that should be used
Some sources of data are..
objective or biased & is not always reliable
The sampling method you choose can greatly influence..
the validity of your conclusions
, Samples may have..
bias & are not always valid
voluntary response sample (aka self-selected sample)
where respondents decide whether or not to be included in the survey/sample
ex. internet surveys, surveys by mail, surveys by phone
practical implications
drawing a sensible conclusion from your results
statistical significance:
statistically there's a difference, the thing is you may have insignificant results
Practical significance..
focuses more on practicality & common sense, something more realistic
statistical thinking
the ability to see the big picture & consider relevant factors such as context, source of data &
sampling to method to form conclusions & identify practical implications. Involved critical
thinking & the ability to make sense of results
Parameter (type of data)
a numerical measurement describing some characteristic of a population
Statistic (type of data)
a numerical measurement describing some characteristic of a sample
Quantitative data
numerical data, based on #'s, representing counts or measurements
ex. dollars, hours, feet, meters, minutes, seconds
Categorical/Qualitative data
data that is not numerical & represents counts or measures
ex. data consisting of names, attributes, etc
Quantitative data types:
discrete data & continuous data
discrete data
