MATH 110 -Statistics (Ch 1)
1.Data: collections of observations
ex. measurements, genders, survey responses, etc
2.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
3.Population: complete collection of all individuals to be studied ex. measurements, scores, people
4.Census: collection of data from every member of the population, collecting data from all individuals 5. Sample: a
subcollection of members selected from a population
data mush be collected through random selection, must be representative of the population
6. 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
7. context: a description of what the values represent, there they came from & why they were collected. It is specific
descriptions for the data provided
8. Always consider the context of data, ...: it affects the statistical analysis that should be used
9. Some sources of data are..: objective or biased & is not always reliable
10. The sampling method you choose can greatly influence..: the validity of your conclusions
11. Samples may have..: bias & are not always valid
12. 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
13. practical implications: drawing a sensible conclusion from your results
14. statistical significance:: statistically there's a difference, the thing is you may have insignificant results
15. Practical significance..: focuses more on practicality & common sense, something more realistic
16. 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
17. Parameter (type of data): a numerical measurement describing some characteristic of a population
18. Statistic (type of data): a numerical measurement describing some characteristic of a sample 19. Quantitative data:
numerical data, based on #'s, representing counts or measurements ex. dollars, hours, feet, meters, minutes, seconds
20 Categorical/Qualitative data: data that is not numerical & represents counts or measures ex. data consisting of names,
attributes, etc
21. Quantitative data types:: discrete data & continuous data
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1.Data: collections of observations
ex. measurements, genders, survey responses, etc
2.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
3.Population: complete collection of all individuals to be studied ex. measurements, scores, people
4.Census: collection of data from every member of the population, collecting data from all individuals 5. Sample: a
subcollection of members selected from a population
data mush be collected through random selection, must be representative of the population
6. 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
7. context: a description of what the values represent, there they came from & why they were collected. It is specific
descriptions for the data provided
8. Always consider the context of data, ...: it affects the statistical analysis that should be used
9. Some sources of data are..: objective or biased & is not always reliable
10. The sampling method you choose can greatly influence..: the validity of your conclusions
11. Samples may have..: bias & are not always valid
12. 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
13. practical implications: drawing a sensible conclusion from your results
14. statistical significance:: statistically there's a difference, the thing is you may have insignificant results
15. Practical significance..: focuses more on practicality & common sense, something more realistic
16. 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
17. Parameter (type of data): a numerical measurement describing some characteristic of a population
18. Statistic (type of data): a numerical measurement describing some characteristic of a sample 19. Quantitative data:
numerical data, based on #'s, representing counts or measurements ex. dollars, hours, feet, meters, minutes, seconds
20 Categorical/Qualitative data: data that is not numerical & represents counts or measures ex. data consisting of names,
attributes, etc
21. Quantitative data types:: discrete data & continuous data
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