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Statistics Introduction Questions with Verified Answers

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Variables - A characteristic (of a person, place, or thing) that takes on different values (achievement, attitude, knowledge, etc.) Types of variables - Quantitative (Numerical) and Qualitative (Categorical Quantitative Variable - Represent differing amounts of the characteristic (age, intelligence, or run time, etc.) Qualitative Variable - Represent differing kinds rather than amounts (gender, marital status, or breed of dog, etc.) Continuous Variables - Variables that can take on any value (number of free throws made, GRE score, or number of students in class) Discrete Variables - Variables that can take a finite number of values (marital status, gender, or a year in school) Dichotomous variable - either male or female Univariate Data - When a study involved studying only one variable (speed) Bivariate Data - When a study involves studying two variables simultaneously (strength and throwing distance) Purpose four levels of measurement - Help the research determine what types of statistical analyses are appropriate for a given set of data Nominal Scale - (Names) Values merely name the category to which the object under study belongs, interpretations are limited to statements of kind rather than amount (Italian, Irish...) Ordinal Scale - Outcomes can be ordered or ranked to reflect differing degrees or amounts of the characteristic being studied (first vs. Second vs. Third) Does not give info about the difference between first and second, second and third Interval Scale - Value assigned is based on some underlying continuum that has equal intervals (The 2-point difference between 3 and 5 and 7 and 8, drop in temp from 30℃ to 10℃ same as 50℃ to 30℃) (Includes meas. of aptitude, achievement, or attitude) Social Sciences Parametric statistical techniques - underlying distributions assumed to be normal

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Institution
Introduction To Statistics
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Introduction to Statistics









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Institution
Introduction to Statistics
Course
Introduction to Statistics

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August 6, 2024
Number of pages
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Written in
2024/2025
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Statistics Introduction Questions with
Verified Answers
Variables - ✅✅ A characteristic (of a person, place, or thing) that takes on
different values (achievement, attitude, knowledge, etc.)

Types of variables - ✅✅ Quantitative (Numerical) and Qualitative (Categorical

Quantitative Variable - ✅✅ Represent differing amounts of the characteristic
(age, intelligence, or run time, etc.)

Qualitative Variable - ✅✅ Represent differing kinds rather than amounts (gender,
marital status, or breed of dog, etc.)

Continuous Variables - ✅✅ Variables that can take on any value (number of free
throws made, GRE score, or number of students in class)

Discrete Variables - ✅✅ Variables that can take a finite number of values (marital
status, gender, or a year in school)

Dichotomous variable - ✅✅ either male or female

Univariate Data - ✅✅ When a study involved studying only one variable (speed)

Bivariate Data - ✅✅ When a study involves studying two variables
simultaneously (strength and throwing distance)

Purpose four levels of measurement - ✅✅ Help the research determine what types
of statistical analyses are appropriate for a given set of data

Nominal Scale - ✅✅ (Names) Values merely name the category to which the
object under study belongs, interpretations are limited to statements of kind rather
than amount (Italian, Irish...)

Ordinal Scale - ✅✅ Outcomes can be ordered or ranked to reflect differing
degrees or amounts of the characteristic being studied (first vs. Second vs. Third)
Does not give info about the difference between first and second, second and third

, Interval Scale - ✅✅ Value assigned is based on some underlying continuum that
has equal intervals (The 2-point difference between 3 and 5 and 7 and 8, drop in
temp from 30℃ to 10℃ same as 50℃ to 30℃) (Includes meas. of aptitude,
achievement, or attitude) Social Sciences

Parametric statistical techniques - ✅✅ underlying distributions assumed to be
normal

Statistics - ✅✅ A set of tools and techniques that are used for describing,
organizing, and interpreting information or data

Example of statistics - ✅✅ Number of students in a particular curriculum speed of
problem-solving, or average cost of dinner

Purpose of statistics - ✅✅ Making decisions with incomplete data

Data - ✅✅ A record of an observation or an event such as a test score, grade in a
class, or response time, one

Data Set - ✅✅ A collection of observations or events such as test scores, grades
on a test, or response times

Descriptive statistics - ✅✅ Used to organize and describe the characteristics of a
collection of data; measures of central tendency (CT) and measures of variability

Inferential statistics - ✅✅ Used to make generalizations from a smaller group of
subjects (a sample to a larger group of subjects (a population); won't have access to
the entire population

Population - ✅✅ A group of people that have at least one characteristic in
common (all aggies)

Sample - ✅✅ A subset of a population (certain subset of aggies)

Statistic - ✅✅ A summarized value of a sample (average age of aggies)

Parameter - ✅✅ A summarized value of a population (average age of the entire
population of aggies)

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