Key Terms- Intro Statistics
Openstax
Rita Head's Group
Key Terms for Intro StatisticsIn statistics, we generally want to study a population. You can think of a population as a collection of persons, things, or
objects under study. To study the population, we select a sample. The idea of sampling is to select a portion (or subset)
of the larger population and study that portion (the sample) to gain information about the population. Data are the result of
sampling from a population.Because it takes a lot of time and money to examine an entire population, sampling is a very practical technique. If you
wished to compute the overall grade point average at your school, it would make sense to select a sample of students who
attend the school. The data collected from the sample would be the students' grade point averages. In presidential elections,
opinion poll samples of 1,000-2,000 people are taken. The opinion poll is supposed to represent the views of the people
in the entire country. Manufacturers of canned carbonated drinks take samples to determine if a 16 ounce can contains 16
ounces of carbonated drink.From the sample data, we can calculate a statistic. A statistic is a number that represents a property of the sample. For
example, if we consider one math class to be a sample of the population of all math classes, then the average number of
points earned by students in that one math class at the end of the term is an example of a statistic. The statistic is an estimate
of a population parameter. A parameter is a number that is a property of the population. Since we considered all math
classes to be the population, then the average number of points earned per student over all the math classes is an example
of a parameter.One of the main concerns in the field of statistics is how accurately a statistic estimates a parameter. The accuracy really
depends on how well the sample represents the population. The sample must contain the characteristics of the population
in order to be a representative sample. We are interested in both the sample statistic and the population parameter in
inferential statistics. In a later chapter, we will use the sample statistic to test the validity of the established population
parameter.A variable, notated by capital letters such as X and Y, is a characteristic of interest for each person or thing in a population.
Variables may be numerical or categorical. Numerical variable stake on values with equal units such as weight in pounds and time in hours.
Categorical variables place the person or thing into a category. If we let X equal the number of points earned by one math student at the end of a term, then X is a numerical variable.If we let Y be a person's party affiliation, then some examples of Y include Republican, Democrat, and Independent. Y
is a categorical variable. We could do some math with values of X (calculate the average number of points earned, for example), but it makes no sense to do math with values of Y (calculating an average party affiliation makes no sense).Data are the actual values of the variable. They may be numbers or they may be words. Datum is a single value.Two words that come up often in statistics are mean and proportion. If you were to take three exams in your math classes
and obtain scores of 86, 75, and 92, you would calculate your mean score by adding the three exam scores and dividing by
three (your mean score would be 84.3 to one decimal place). If, in your math class, there are 40 students and 22 are men
and 18 are women, then the proportion of men students is 22/40 and the proportion of women students is 18/40.Download for free at
http://cnx.org/content/col11562/latest/
objects under study. To study the population, we select a sample. The idea of sampling is to select a portion (or subset)
of the larger population and study that portion (the sample) to gain information about the population. Data are the result of
sampling from a population.Because it takes a lot of time and money to examine an entire population, sampling is a very practical technique. If you
wished to compute the overall grade point average at your school, it would make sense to select a sample of students who
attend the school. The data collected from the sample would be the students' grade point averages. In presidential elections,
opinion poll samples of 1,000-2,000 people are taken. The opinion poll is supposed to represent the views of the people
in the entire country. Manufacturers of canned carbonated drinks take samples to determine if a 16 ounce can contains 16
ounces of carbonated drink.From the sample data, we can calculate a statistic. A statistic is a number that represents a property of the sample. For
example, if we consider one math class to be a sample of the population of all math classes, then the average number of
points earned by students in that one math class at the end of the term is an example of a statistic. The statistic is an estimate
of a population parameter. A parameter is a number that is a property of the population. Since we considered all math
classes to be the population, then the average number of points earned per student over all the math classes is an example
of a parameter.One of the main concerns in the field of statistics is how accurately a statistic estimates a parameter. The accuracy really
depends on how well the sample represents the population. The sample must contain the characteristics of the population
in order to be a representative sample. We are interested in both the sample statistic and the population parameter in
inferential statistics. In a later chapter, we will use the sample statistic to test the validity of the established population
parameter.A variable, notated by capital letters such as X and Y, is a characteristic of interest for each person or thing in a population.
Variables may be numerical or categorical. Numerical variable stake on values with equal units such as weight in pounds and time in hours.
Categorical variables place the person or thing into a category. If we let X equal the number of points earned by one math student at the end of a term, then X is a numerical variable.If we let Y be a person's party affiliation, then some examples of Y include Republican, Democrat, and Independent. Y
is a categorical variable. We could do some math with values of X (calculate the average number of points earned, for example), but it makes no sense to do math with values of Y (calculating an average party affiliation makes no sense).Data are the actual values of the variable. They may be numbers or they may be words. Datum is a single value.Two words that come up often in statistics are mean and proportion. If you were to take three exams in your math classes
and obtain scores of 86, 75, and 92, you would calculate your mean score by adding the three exam scores and dividing by
three (your mean score would be 84.3 to one decimal place). If, in your math class, there are 40 students and 22 are men
and 18 are women, then the proportion of men students is 22/40 and the proportion of women students is 18/40.Download for free at
http://cnx.org/content/col11562/latest/