what is statistics statistics can be defined as the collection and interpretation of data all around the world we use statistics to measure and analyze variability people have different heights weights hair color food preferences and so on these things are all variable because they change among different individuals there are two kinds of Statistics there is inferential statistics and there is descriptive statistics inferential statistics deals with taking a sample and analyzing that sample to make judgments or claims about a population descriptive statistics refers to getting data and talking about it so when you hear a professor say something like the average midterm score was 65% they are using descriptive statistics we often use things like histograms and graphs to help us summarize and explain descriptive statistics the first part of the course deals with descriptive statistics and the second part of the course deals with inferential statistics in order to understand statistics you'll first have to know some basic definitions a population refers to the total amount of things I say things because a population can refer to almost anything this can refer to the total amount of people cats vehicles houses and so on now a sample refers to a small part of the population that is used for study and the total amount of things in a sample is called the sample size in statistics what we examine is a variable it is what we are studying and it can be measurable countable and categorized when we talked about how people can have different heights weights and hair color these are all variables variables represent a characteristic of what we are trying to study and they can vary among different individuals when we measure a variable our data can come into two different forms there is categorical data and there is quantitative data quantitative data refers to data that is measured in numbers it deals with numbers that make sense to perform arithmetic calculations with like calculating an average quantitative data comes from quantitative variables examples include height weight and Midterm score on the other hand categorical data refers to values that place things into different groups or categories categorical data comes from categorical variables examples include hair color type of cat and letter grade there are actually two types of categorical variables there is categorical and ordinal and categorical and nominal something is said to be categorical and ordinal if there is a logical ordering to the values of a categorical variable a good example of this would be letter grade we can logically order the values of this categorical variable from high to low or from low to high now something is said to be categorical and nominal if there is no logical ordering to the values of a categorical variable an example of this would be hair color depending on our sample we could have people with red hair blonde hair brown hair or even blue hair although we can arrange these values in alphabetical order there is no logical ordering with respect to the actual values itself there are also two types of quantitative variables there's discret and continuous discret variables refer to variables that can only be measured in certain numbers an example of this is the number of pets you own you can own zero pets one pet two pets or even 30 pets but it's impossible for us to own 2.7 pets in contrast continuous variables refer to variables that can take on any numerical value an example of this would be weight someone can weigh 105 lb 185 lb or even 170. 683 lb we can measure this variable in as many decimal places as we want which is why it is classified as a continuous variable so to recap a population refers to the total number of things a sample refers to a small part of the population that we examine and extract information from the total number of things in a sample is called a sample size what we measure from each individual is the variable of interest the way we measure these variables lets us know if the variable is quantitative or categorical for example if our variable of interest was midterm scores for statistics we would have quantitative data if we measure each individual's test score if instead we decide to place people into categories based on letter grade then we would be working with categorical data