2. 8.1 Introduction to Statistics

3. Students will learn key Vocab
Objectives
Students will learn key Vocab
Students will different types of sampling
Students will know misuses of statistics

4. Two categories of data
Quantitative Data
are numbers that indicate amounts, differences, or counts.
vs.
Qualitative Data
are generally words that indicate observations and are indicative of differences in kind.

5. Examples Quantitative versus Qualitative Data
What is your age?
The data provided in this instance should be numbers of years and thus would be quantitative.

6. Examples Quantitative versus Qualitative Data
What is your intended major?
The data in this instance should be the name of an area of study such as mathematics. This type of data is qualitative.

7. Examples Quantitative versus Qualitative Data
What is your SAT score?
The word score typifies quantitative.

8. Examples Quantitative versus Qualitative Data
What is your gender?
We would expect the answer to be male or female. This is qualitative data.

9. Examples Quantitative versus Qualitative Data
What is your telephone number?
Although the answer to this question involves number, they do not represent a count or amount-only a particular phone line or location. This is qualitative data.

11. a small part or quantity intended to show what the whole is like.
Sample and Population
Sample
a small part or quantity intended to show what the whole is like.
Population
a complete set of observations.

13. Type of Sampling Method
Stratified sampling
Simple Random sampling
Cluster sampling
Systematic sampling
Convenience sampling

14. Stratified Sampling
the population is divided into distinct group or classes inside a population that share a common characteristic called strata
Example
Obtain a list of patients discharged from all MMH facilities. Divide the patients according to length of hospital stay(3 days or less, 4-7 days, 8-14 days). Draw random samples from each group
Discharged patients divided into groups depending on number of days on hospital

15. Simple Random Sampling
every member of the population has an equal probability of being selected.
Example
Obtain a list of patients discharged from all MMH facilities. Number these patients and then use a random number table to obtain a sample.
Random number table

16. Cluster Sampling
begin by dividing the demographic area into sections, then randomly select sections and survey all individuals in those sections.
Example
Randomly select some MMH facilities from each of five geographic regions and then survey all patients discharged from each hospital.
Geographic regions

17. Systematic Sampling
it is assumed that the elements of the population are arranged in some natural sequential order. Then a random starting point is selected and we select every “nth” element for our sample.
Example
At the beginning of the year, instruct each MMH facility to survey every 500th patient discharged
every 500th patient

18. Convenience Sampling
uses results or data that are conveniently and readily obtained.
Example
Instruct each MMH facility to survey 10 discharged patients this week and send in the results.
any 10 discharged patients in one week

19. Misuses of Statistics

20. Coke funding Scientists
Bias is the difference between the results obtained by sampling and the truth about the whole population

21. Misuses of Statistics

22. Misuses of Statistics

23. Extra Vocab for HW #1-4
Observational study is when a researcher gathers data by watching a sample of the population and collecting information.
Experimental Study is when a researcher surveys a sample of the population and then manipulates or treats it in some way.
Statistical Study are used to collect quantitative info from a specific group.

24. Extra Vocab for homework #5-10
Descriptive statistics classifies, sorts and summarizes data.
Inferential Statistics is a conclusion or presumption that is made based on reasoning from the evidence that is available.