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0:00 in this video we're gonna talk about the differences between a statistic and a parameter but first what do you think the difference is between the two statistics are characteristics that describe a sample parameters are characteristics that describe the population now you need to know the difference between a sample and the population the population will represent everyone or everything in a study the sample is basically a subset of the population it's a small portion of the
0:45 population so let's say in town XYZ we have a hundred thousand people and let's say we wish to estimate the average age of the one hundred thousand residents in town X Y Z now it's going to be a lot of work to get the age of each individual and average all of their ages but instead let's say if we talk to a hundred individuals out of the 100,000 ask for their ages and then take the average so the average age of those 100
1:33 individuals would be the sample mean so that is a statistic the true average age of all of the 100,000 residents of town X Y Z that would be the population mean that's a parameter so the sample is a small subset of the population the population is a hundred thousand but the sample that we chose is only a hundred individuals out of the population of 100,000 so hopefully that helps you to see the difference between a sample and a population now let's talk about some variables that
2:18 would also highlight the differences between statistics and parameters so this symbol represents the sample mean so that would be a statistic because it describes the mean of the sample that symbol mu is the mean of the population that's a parameter it's a characteristic of the population S stands for the standard deviation of a sample so that would be a statistic Sigma is the standard deviation of the population that's a parameter S squared represents the sample variance Sigma squared is the
3:07 variance of the population so that's a parameter next we have proportions the sample proportion is simply P hat and the parameter I mean excuse me the population proportion is simply P finally we have the sample size well let me just say the size the size of the sample is represented by the symbol lowercase n so that would be a statistic the size of the population is represented by the symbol capital n so that is a parameter so hopefully these symbols will help you to see the
3:55 difference between a statistic and a parameter now let's take a brief quiz so for each of these statements determine if it describes a statistic or a parameter number one the average weight of all males in the United States is that a statistic or parameter what would you say now remember a parameter would describe everyone in the group a statistic would describe only some of the individuals in the group so for number one we're dealing with the weight of all the mills in the US so that is a parameter number to the
4:50 average height of 100 cats in the state of California California have millions of people and in the whole state there's millions of cats so if we're calculating the average height of a hundred cats we're calculating the height of a small subset of the entire population so this would be a statistic because our study involves just a small portion of the entire population number three the average test of 20 students in the class of 500 in that class the population will be the 500 that's everyone in the class but our study involves only 20 out of the 500 so it's taken a small sample
5:36 from that population this would be a statistic number for the average test score of all students in the class so that is the entire population of everyone in the class so the average test score would be a parameter so since we're dealing with averages or mean the symbol for number one would be meal and the same is true for number four for two and three the symbol would be x-bar to represent the sample mean so that's it for this video so now you know the difference between a statistic and a parameter and you also know the difference between a sample and the population thanks again for watching
