1. Chapter 11.0 Why Study Statistics? Statistics is the study of collecting, displaying, analyzing, and interpreting information. Information that was collected in a careful and systematic way is called data. We can use that data to better understand the world, and make better decisions about how we live.

2. A population is a collection of all outcomes, responses, measurements, or counts that are of interest. A sample is a subset of a population.

3. Is it an example of a Population or a Sample? 1.The age of all High School principals. 2.The color of hair of every 4 th girl that leaves a salon. 3.A survey of 300 students out of 1000 Liberty Students. 4.The average salary of a Liberty teacher.

4. Sampling Techniques A random sample is one in which every member of the population has an equal chance of being selected. A convenience sample is one that consists of only easily available subjects.

5. Sampling Techniques Systematic sample Each member of the population is assigned a number Members of the population are ordered Samples are taken from the population at regular intervals (ie: every 3 rd, or 25 th etc. individual)

6. Sampling Techniques Systematic Sample Example: Every 3 rd individual is in this sample

7. Sampling Techniques Stratified Sample Has members of each segment of the population Members are divided into subsets called strata, sharing similar characteristics, such as age, gender, ethnicity A sample is randomly selected from each strata Ensures that each segment of the population is represented

8. Sampling Techniques Stratified Sample Example

9. Sampling Techniques Self-selected (Volunteer) Sample: Subjects from the chosen population volunteer to be in the sample. Example: You post a question on social media to vote on a list of formal themes.

10. Biased Sampling If you are not careful about how you choose your sample, you can introduce bias into your data. Bias is a systematic favoring of one outcome. Example: You ask your classmates in Advanced Algebra what theme should be used for prom.

11. Biased Sampling To avoid bias, you want to have a sample that is representative of the whole population. A representative sample is a small group from the population that is like the population in some important way. Example: You take a random sample of students at liberty to decide what theme should be used for prom.

12. Which sampling technique is used? Is the sample biased (non-representative? 1.Using Liberty student ID numbers, you randomly select 100 students. 2.You select Liberty students in your Advanced Algebra class. 3.You sort students by their student ID number, then select every 50 th student. 4.Using student ID numbers, you randomly select 25 students from each class; Freshmen, Sophomores, Juniors, and Seniors.