1. Chapter 1 Introduction to Statistics

2. 1.1 An Overview of Statistics

3. Definitions:
Data – consists of information coming form observations, counts, measurements, or responses
Population – the complete collection of individuals to be studied
Sample – part of a population
Statistics – the science of collecting, organizing, analyzing, and interpreting data in order to make decisions

4. EX: Identify the population and the sample
In a recent survey, 614 small business owners in the U.S. were asked whether they thought their companies Facebook presence was valuable.
The U.S. Department of Energy conducts weekly surveys of approximately 800 gas stations to determine the average price per gallon of regular gas.

5. Definitions: Parameter – a numerical description of a population
Statistic – a numerical description of a sample

6. EX: Determine whether the numerical value is a parameter or a statistic.
A recent survey of approximately 400,000 employers reported that the average starting salary for marketing majors is $53,000.
The freshman class at a university has an average SAT math score of 514.
In a random check of 400 retail stores, the FDA found that 34% of the stores were not storing fish at the proper temperature.

7. Branches of Statistics
Descriptive Statistics – the branch of stats that involves the organization, summarization, and display of data.
Inferential Statistics – the branch of stats that involve using a sample to draw conclusions about a population

8. EX:
A large sample of men, aged 48, was studied for 18 years. For unmarried men, approximately 70% were alive at age 65. For married men, 90% were alive at age 65.
A) Which part of the study represents descriptive statistics?
B) What conclusions might be drawn from the study using inferential statistics?

9. 1.2 Data Classification

10. Types of Data
Qualitative Data – consists of attributes, labels, or nonnumerical entries
EX: Names of Basketball Players
Quantitative Data – consists of numerical measurements or counts
EX: Heights of Basketball Players

11. EX:

12. EX: Determine whether the data is qualitative or quantitative.
Jersey numbers of soccer players
Mile times of runners
Hair color of your classmates

13. Levels of Measurement Nominal – Qualitative data only
No math computations can be done with data
EX: names of colleges
Ordinal – Qualitative or quantitative data
Data can be ordered but differences are meaningless
EX: Top 10 Colleges in the U.S.

14. Interval – Quantitative data only
Data can be ordered, differences are meaningful, but there is no natural zero starting point (where none of the quantity is present)
EX: Years
Ratio – Quantitative data only
Data can be ordered, differences are meaningful, there is a natural zero starting point, and ratios are meaningful
EX: Money in your wallet

16. EX: Determine the level of measurement.
The final standings for the Pacific Division of the NBA
A collection of phone numbers
The hourly body temperatures of a preemie in the NICU
The heart rates (in beats per minute) of a preemie in the NICU

17. 1.3 Data Collection and Experimental Design

18. Statistical Studies
Goal: To collect data and then use the data to make a decision about the whole population.
Note: Any decision that is made using the results is only as good as the process used to obtain the data
If the process is flawed…the results will be questionable

19. Types of Studies
Observational – a researcher does not influence the responses
Just observations are made
No changes are made to existing conditions

20. Types of Studies
Experiment – a researcher deliberately applies a treatment before observing the responses
Treatment Group – part of the population that receives the treatment
Control Group – part of the population that does not receive the treatment
Experimental Units – all subjects in both groups
Placebo – a fake treatment, that is made to look like the real treatment, often given to the control group

21. EX: Determine whether the study is an observational study or an experiment.
Researchers study the effect of vitamin D supplementation among patients with antibody deficiency or frequent respiratory tract infections. To perform the study, 70 patients receive 4000 IU of vitamin D daily for a year. Another group of 70 patients receive a placebo daily for one year.

22. Researchers conduct a study to find the U. S
Researchers conduct a study to find the U.S. public approval rating of the U.S. president. To perform the study, researchers call 1500 U.S. residents and ask them whether they approve or disapprove of the job being done by the president.

23. Data Collection
Simulation – the use of a mathematical or physical model to reproduce the conditions of a situation or process.
EX: Car crashes
Survey – an investigation of one or more characteristics of a population
EX: Asking people questions
Make sure questions are worded in a way that does not lead to biased results

24. Experimental Design
To produce meaningful and unbiased results, experiments should be carefully designed and executed.
Elements of a well-designed experiment:
1) Control
2) Randomization
3) Replication

25. 1) Control Influential factors must be controlled:
Confounding variable – occurs when an experimenter cannot tell the difference between different factors on the variable
EX:

26. Techniques to minimize the placebo effect:
Placebo effect – when a subject reacts favorably to a placebo when in fact the subject was given a fake treatment
Techniques to minimize the placebo effect:
Blinding – the subjects do not know whether they are receiving a treatment or placebo
Double- Blinding – neither the experimenter nor the subjects know

27. 2) Randomization
A process of randomly assigning subjects to different treatment groups
Completely randomized design – treatment groups chosen by random selection
Blocks – groups of subjects with similar characteristics
Randomized block design – subjects with similar characteristics separated into blocks. Subjects form each block are then randomly chosen.

28. Randomized block design example:

29. Matched-pairs design – subjects are paired up according to similarity (age, location, physical characteristics…)
One person in the pair receives the treatment and the other receives the placebo
EX:

30. 3) Replication
The repetition of an experiment under the same or similar conditions.
Sample size – the number of subjects in a study
EX:

31. EX:
A company wants to test the effectiveness of a new gum developed to help people quit smoking. Identify a potential problem with the given experimental design and suggest a way to improve it:
A company identifies ten adults who are heavy smokers. Five are given the new gum and the other five are given a placebo. After two months, the subjects are evaluated and it is found that the five subjects using the new gum have quit smoking.

32. The company identifies 1,000 adults who are heavy smokers
The company identifies 1,000 adults who are heavy smokers. The subjects are divided into blocks according to gender. Females are given the new gum and males are given the placebo. After two months, a significant number of the female subjects have quit smoking.

33. The company identifies 240 adults who are heavy smokers
The company identifies 240 adults who are heavy smokers. The subjects are randomly assigned to be in a treatment group or in a control group. Each subject is also given a DVD featuring the dangers of smoking. After 4 months, most of the subjects in the treatment group have quit smoking.

34. Sampling Techniques
Census – a count or measure of the entire population
Sampling – a count or measure of part of the population
Must be representative of the entire population
If it is not representative of the population, a sampling error has occurred.

35. Sampling Techniques
Random sample – every member of the population has an equal chance of being selected
Simple random sample – every possible sample of the same size has the same chance of being selected
To collect a SRS:
Assign a number to each member of the population
Then use a calculator or computer program to generate random numbers

36. EX:
There are 731 students enrolled in a stats course at your school. You wish to form a sample of 8 students to answer some survey questions. Select the students who will belong in the SRS using your calculator.

37. Other sampling techniques:
Stratified sample – population is divided in to two or more subsets, called strata, that share similar characteristics. A sample is then randomly selected from each strata.
EX:

38. Cluster sample – population is divided into groups, called clusters, and all members in one or more clusters are selected
EX:

39. Systematic sample – each member of the population is assigned a number
Systematic sample – each member of the population is assigned a number. Members are ordered and selected at regular intervals
EX: every 3th person

40. Convenience sample – consists of members of the population that are easy to get
Often biased so not recommended
EX: asking your friends around you

41. EX:
You are doing a study to determine the opinions of students at your school regarding stem cell research. Identify the sampling technique used. Discuss any bias (if any).
You divide the student population with respect to majors and randomly select and question some students in each major.

42. You assign each student a number and generate random numbers
You assign each student a number and generate random numbers. You then question each student whose number is randomly selected.
You select students who are in your biology class.

43. You select a class at random and question each student in the class.
You assign each student a number and, after choosing a starting number, question every 25th student.