Statistics - A Full University Course on
Data Science Basics
Monica wahi: What is statistics ? Statistics is the study how to collect,
organize, analyze and interpret numerical information and data.
Statistics is both the science of uncertainty and the technology of
extracting information from data. At the end of this lecture, students
should be able to state at least one definition of statistics. Statistics is
used to help us make decisions, not just whether to go to the
restaurant or not, but important statistics in health care and public
health. Individuals are people or objects included in a study. The only
variable is I do n't know what time something is going to happen. A
variable then is a characteristic of the individual to be measured or
observed. Statistics is used in healthcare and other disciplines to aid in
decision making. And so therefore, it 's really important to understand
statistics , because you need to understand these processes in
healthcare. And we 're going on to talk about what a population
parameter is , and what a sample statistic is.
Population is a group of people or objects with a common theme.
When every member of that group is considered this population. The
population is every single individual in there. The sample is a small
portion of that population. It can be a representative sample, but it can
also be a biased sample. In sample data, the data is only available
from some of the individuals in the population. But in sample data ,
the data are only available in statistics. In the U. S. every 10 years, the
government hires a bunch of people to go out and survey a lot of
people. And also, they send out a whole lot of surveys. And that's
called the United States Census. The United States Census only takes
place every 10 years. Hurricane Katrina changed the population
distribution in Louisiana and other states around there. So how did
they keep up ? Well, they used the American Community Survey. The
US does n't know exactly how many people would be in Louisiana or
anywhere else. But they can use statistics to extrapolate that back to
the population of Medicare beneficiaries.
When you're practicing in the field of statistics, it 's very
important to point out when the number you 're talking about
comes from a population versus a sample. So for example, the
mean age of every American on Medicare is a parameter that 's
every single person. However, remember , the Medicare
beneficiary survey is just a sample of the population. So you
should really use the term. This is a. parameter if it. s from a.
population , or this is a statistic , if it's from a sample, if it is
based on a population. In inferential statistics involves
methods of using information from a sample to draw
conclusions regarding the population. Inferential statistics can
Data Science Basics
Monica wahi: What is statistics ? Statistics is the study how to collect,
organize, analyze and interpret numerical information and data.
Statistics is both the science of uncertainty and the technology of
extracting information from data. At the end of this lecture, students
should be able to state at least one definition of statistics. Statistics is
used to help us make decisions, not just whether to go to the
restaurant or not, but important statistics in health care and public
health. Individuals are people or objects included in a study. The only
variable is I do n't know what time something is going to happen. A
variable then is a characteristic of the individual to be measured or
observed. Statistics is used in healthcare and other disciplines to aid in
decision making. And so therefore, it 's really important to understand
statistics , because you need to understand these processes in
healthcare. And we 're going on to talk about what a population
parameter is , and what a sample statistic is.
Population is a group of people or objects with a common theme.
When every member of that group is considered this population. The
population is every single individual in there. The sample is a small
portion of that population. It can be a representative sample, but it can
also be a biased sample. In sample data, the data is only available
from some of the individuals in the population. But in sample data ,
the data are only available in statistics. In the U. S. every 10 years, the
government hires a bunch of people to go out and survey a lot of
people. And also, they send out a whole lot of surveys. And that's
called the United States Census. The United States Census only takes
place every 10 years. Hurricane Katrina changed the population
distribution in Louisiana and other states around there. So how did
they keep up ? Well, they used the American Community Survey. The
US does n't know exactly how many people would be in Louisiana or
anywhere else. But they can use statistics to extrapolate that back to
the population of Medicare beneficiaries.
When you're practicing in the field of statistics, it 's very
important to point out when the number you 're talking about
comes from a population versus a sample. So for example, the
mean age of every American on Medicare is a parameter that 's
every single person. However, remember , the Medicare
beneficiary survey is just a sample of the population. So you
should really use the term. This is a. parameter if it. s from a.
population , or this is a statistic , if it's from a sample, if it is
based on a population. In inferential statistics involves
methods of using information from a sample to draw
conclusions regarding the population. Inferential statistics can
