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1. Introduction to Statistics (Key Principles of the Statistical Method) Exam Questions and Answers 2024/2025( A+ GRADED 100% VERIFIED).

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1. Introduction to Statistics (Key Principles of the Statistical Method) Exam Questions and Answers 2024/2025( A+ GRADED 100% VERIFIED).

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1. Introduction to Statistics (Key
Principles of the Statistical Method)
Steps of statistics - ANS 1. Collect. Collect the information from a variety of sources
2. Analyze. Analyze the information that you've collected
3. Interpret. Interpret what that analysis means
4. Present. Present it in a way that anyone can understand

Descriptive statistics - ANS Using only the information at hand to describe the selected group of
individuals

Inferential statistics - ANS Using the information at hand to make a larger, more general
statement about the entire population of
individuals

Statistical analysis - ANS All the ways of collecting, analyzing, and interpreting the data

Statistical study - ANS A way to collect information from individuals

Statistics - ANS The study of collecting, analyzing, interpreting, and presenting information

Available Data - ANS Data collected by some other entity - a government organization or
private company.

Raw Data - ANS Unorganized, unprocessed, and not summarized. Typically, this is data that is
not already available.

Bias - ANS The systematic favoring of certain outcomes in a study. There are many ways to
introduce bias into a study.

Data - ANS Information used in a study to answer a statistical question

Qualitative (Categorical) Data - ANS Data that describes. It can't be measured or used for
arithmetic.

Data whose values are the names of categories. These can be numbers, but not the kinds of
numbers with
which makes sense to do any numerical operations.

, Nominal Level of Measurement - ANS Qualitative data where the order in which the categories
are presented does not matter.

Ordinal Level of Measurement - ANS Qualitative data where the order in which the categories
are presented matters.

Quantitative (Numerical) Data - ANS Data that is numerical. It can be measured and it can be
used for arithmetic. .

Data whose values are numbers and it makes sense to do numerical operations.
ex. Weight, commute time to work, outdoor temp

Nominal Data - ANS Categorical data with qualities that cannot be ordered or ranked.

Ordinal Data - ANS Categorical data with qualities that can be ordered or ranked.

Discrete Data - ANS Quantitative Data that can only take so many different values.

Can only take whole number values (can't have half a pet).

Continuous Data - ANS Quantitative data that can take any value within an interval.

eg. temperature, commute time, and wait (can take on any value within a range).

Population - ANS The entire set of individuals from which to sample.

Census - ANS Using the entire population to obtain data.

Sample/Sampling - ANS a subset of the population and you would obtain data from that subset
and leave everyone else out. There are many ways to select a sample

representative sample - ANS A sample that accurately reflects the population.

random sample - ANS A sample that has been selected in a manner where every member of
the population has some
predetermined chance of being selected for the sample.

Random Selection - ANS The method of obtaining a random sample.

Probability Sampling Plan - ANS The way to collect a random sample that guarantees a certain
likelihood for each member of the population to be selected.

Might you get something that's unrepresentative? Yes. But the vast majority of the time, it will be
representative.

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Subido en
10 de octubre de 2024
Número de páginas
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Escrito en
2024/2025
Tipo
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