1. Warm-Up Honors Algebra 2 4/2/19
A marketing company located in Hollywood, CA is really curious to see which group of U.S. high school students spends the most time watching t.v. every day. For some reason, they decided to take data from your high school only. After randomly selecting 25 students, they find that ninth graders watch the most t.v. per day. What is the sample of the population?
All high school students in the U.S.A.
All high school students in California
All high school students in your school
25 high school students from your school
2. Explain your reasoning for your answer for #1.
Correct Answer:
25 high school students from your school
Answer Explanation:
The population in question consists of all the high school students in the United States, but it's unrealistic to sample them all. The sample is the smaller group from which the analysts collect data. In this case, they only selected 25 students from your school to represent the entire population of U.S. high school students. That probably won't give them the most accurate data, but that was the sample they chose.

2. Population- the entire group that is being studied
Population- the entire group that is being studied. The population can be people, animals, or objects.
Sample- A small portion of the population.
A population can be all the people in the world, tenth-grade girls in the United States, giraffes in Africa, or trees in Oregon. A researcher must clearly define a population that he or she wants to study. If the population is too large, a sample is studied. If the sample is chosen correctly, it will be representative of the population, so the information gathered from the sample will be similar to information about the population.

3. Population
It is the entire group we are interested in, which we wish to describe or draw conclusions about.

4. Random sampling is a method in which people are chosen “out of the blue.” In a true random sample, everyone in the population must have the same chance of being chosen. It is important that each person in the population has a chance of being picked.
Ex) Use a sample of students as they walk down the hall by the office.

5. Stratified sampling is a method actively seeking to poll people from many different backgrounds. The population is first divided into different categories (or strata) and the number of members in each category is determined.
Ex) Use a sample of 2 random 9th, 10th, 11th and 12th graders coming out of English class each period.

6. Biased Samples
If the sample ends up with one or more sub-groups that are either over- represented or under- represented, then we say the sample is biased.

7. Parameter- characteristic of the population
Statistic- a characteristic of a sample.
A parameter is often unknown, since information from the entire population can be impossible to gather. Imagine trying to find the mean height of every person in the world. Statisticians use information from samples to estimate a parameter, and different samples may produce different statistics. The mean height of different samples is variable; it can change. However, the parameter does not change. Often, statisticians use many statistics from different samples to estimate the parameter.

8. Descriptive statistics- summarizes data
Descriptive statistics- summarizes data. This includes mean, median, mode, range, and standard deviation. Summaries are often represented in tables and graphs.
Inferential statistics- draws conclusions about a population based on data from a sample.
Consider studying the heights of 10th graders in the United States. You might collect data from a random group of students in each state, you are using descriptive statistics. If you then take the mean of all the means in the table, you may use that mean to estimate the mean height of all 10th graders in the population, including the students who were not in the sample. This estimate is an example of an inferential statistic.