• Study Resource
  • Explore
    • Arts & Humanities
    • Business
    • Engineering & Technology
    • Foreign Language
    • History
    • Math
    • Science
    • Social Science

    Top subcategories

    • Advanced Math
    • Algebra
    • Basic Math
    • Calculus
    • Geometry
    • Linear Algebra
    • Pre-Algebra
    • Pre-Calculus
    • Statistics And Probability
    • Trigonometry
    • other →

    Top subcategories

    • Astronomy
    • Astrophysics
    • Biology
    • Chemistry
    • Earth Science
    • Environmental Science
    • Health Science
    • Physics
    • other →

    Top subcategories

    • Anthropology
    • Law
    • Political Science
    • Psychology
    • Sociology
    • other →

    Top subcategories

    • Accounting
    • Economics
    • Finance
    • Management
    • other →

    Top subcategories

    • Aerospace Engineering
    • Bioengineering
    • Chemical Engineering
    • Civil Engineering
    • Computer Science
    • Electrical Engineering
    • Industrial Engineering
    • Mechanical Engineering
    • Web Design
    • other →

    Top subcategories

    • Architecture
    • Communications
    • English
    • Gender Studies
    • Music
    • Performing Arts
    • Philosophy
    • Religious Studies
    • Writing
    • other →

    Top subcategories

    • Ancient History
    • European History
    • US History
    • World History
    • other →

    Top subcategories

    • Croatian
    • Czech
    • Finnish
    • Greek
    • Hindi
    • Japanese
    • Korean
    • Persian
    • Swedish
    • Turkish
    • other →
 
Profile Documents Logout
Upload
Populations
Populations

... • The MEAN is the arithmetic average of the set of observations (can be used for both continuous and discrete data) • can be susceptible to influence of outliers (income example) ...
1.1 Basic Equations
1.1 Basic Equations

... Inferential Stats: making predictions or inferences about a population based on a sample ...
Descriptive Measures
Descriptive Measures

... they are of little value in practical prediction situations.  With correlation around 0.50, crude group prediction may be achieved. In describing the relationship between two variables, correlation coefficients that are this low do not suggest a good relationship.  Correlation coefficients ranging ...
Describing the Spread of Quantitative Data
Describing the Spread of Quantitative Data

... numbers or letters assigned to objects serve as labels for identification or classification. • For example, names and gender are categorical variables; – and one can put the level ‘M’ for Male and ‘F’ for Female, – or ‘1’ for male and ‘2’ for female, – or ‘1’ for female and ‘2’ for male. ...
In Depth: Descriptive Research
In Depth: Descriptive Research

... Examples: finishers in a race, class ranking, small, medium, and large size Interval order and equal distance, but no true zero Zero is not the absence of the property Examples: Intelligence, degrees F or C ...
BIOSTATISTICS QUIZ ANSWERS
BIOSTATISTICS QUIZ ANSWERS

... a. False: Tests the null hypothesis that the mean of the differences in the population is zero. b. True (This is required in order to calculate the difference for each pair of observations.) c. False: the paired t-test makes the assumption that the differences between the pairs are normally distribu ...
1. For a particular sample of 63 scores on a psychology exam, the
1. For a particular sample of 63 scores on a psychology exam, the

... 8. SAT I scores around the nation tend to have a mean scale score around 500, a standard deviation of about 100 points and are approximately normally distributed. A person who scores 700 on the SAT I has approximately what percentile rank within the population? Show all work as to how this is obtain ...
Chapter 3 Slides (PPT)
Chapter 3 Slides (PPT)

... been ordered from smallest to largest. Appropriate for interval and ordinal scales • Pth percentile - Value where P% of measurements fall below and (100-P)% lie above. Lower quartile(25th), Median(50th), Upper quartile(75th) often reported • Mode - Most frequently occurring outcome. Typically report ...
Bivariate Data
Bivariate Data

...  Are there any unusual points? Outliers are points whose combination of values is unusual. They will affect what we perceive as the pattern, so they need investigation. If the data points fit a straight line well, we can use one of the variables to predict the other. Usually, one variable is diffic ...
Regression
Regression

... Regression: When you did your excel graphs on variables from the Class Vital Data, you put in a trend line and the R2 value. The R2 value is called “R squared” by scientists. It tells how closely the data are clustered around the trendline, or the strength of the regression. This clustering is a mea ...
KING ABDULAZIZ UNVERSITY
KING ABDULAZIZ UNVERSITY

... If a variable can take any value between 0 and 15, then this variable is called a …….. variable. (A) continuous (C) discrete and quantitative (B) discrete (D) continuous and qualitative ...
data prep and descriptive stats
data prep and descriptive stats

... • The process of systematically and consistently assigning each response a numerical score. • The key to a good coding system is for the coding categories to be mutually exclusive and the entire system to be collectively exhaustive. • To be mutually exclusive, every response must fit into only one c ...
AP Stats Chapter1 Powerpoint
AP Stats Chapter1 Powerpoint

... Copyright © 2007 by W. H. Freeman & Company ...
ANOVA & Regression
ANOVA & Regression

... The bigger the test statistic the more likely there is a relationship between the independent and dependent variables. Values greater than 3 are for every type of inferential statistic other than correlation are usually statistically significant. Relationships can be positive or negative. You need t ...
ANOVA & Regression
ANOVA & Regression

... The bigger the test statistic the more likely there is a relationship between the independent and dependent variables. Values greater than 3 are for every type of inferential statistic other than correlation are usually statistically significant. • Relationships can be positive or negative. You need ...
Chapter 3 outline notes
Chapter 3 outline notes

... • Cross classifications of categorical variables in which rows (typically) represent categories of explanatory variable and columns represent categories of response variable. • Numbers in “cells” of the table give the numbers of individuals at the corresponding combination of levels of the two varia ...
Chapter 1 Study Guide
Chapter 1 Study Guide

... 2. Explain how to calculate the mean, x . 3. Explain how to calculate the median, M. 4. Explain why the median is resistant to extreme observations, but the mean is nonresistant. 5. In statistics, what is meant by spread? 6. Explain how to calculate Q1 and Q3. 7. What is the five-number summary? 8. ...
META-ANALYSIS OF RESEARCH
META-ANALYSIS OF RESEARCH

...  Procedures for reliability of coding  Data analysis approach (eg. Lipsey & Wilson) ...
KING ABDULAZIZ UNVERSITY
KING ABDULAZIZ UNVERSITY

... Please: Make sure that the answer sheet form matches the question form. ...
Handout for SPSS
Handout for SPSS

... grouping variables. All levels of the grouping variable are crosstabulated. You can choose the order in which the statistics are displayed. Summary statistics for each variable across all categories are also displayed. Data values in each category can be listed or suppressed. With large data sets, y ...
chapter2A
chapter2A

... Studentized residuals – standardizing the residuals using the standard deviation of the data with the individual omitted from the data (helps to avoid having too big a standard deviation) Beware of lurking variables Correlation measures only linear association. Extrapolation can be inaccurate. Corre ...
Review Topics for
Review Topics for

... prediction problems in XLMINER? What are some of the other predictive accuracy measures one could use? What loss function is implied by the RMSE accuracy measure in prediction problems? You should know the basic logic of the various data mining techniques. With respect to multiple linear regression ...
one-way anova
one-way anova

... Interaction effects(two indep. Variables separated by *): if Sig. less than 0.05 it means there is interaction effect—there is significant difference in first independent variable GIVEN the second one. Main Effects—check each of the indep. Variables and their Sig. value; if less than 0.05, that vari ...
10 Chapter 01 Concept Sheet
10 Chapter 01 Concept Sheet

... the median M is the center observation in the ordered list. The position of the center can be found at (n +1)/2.  If the number of observations n is even, the median M is the mean of the two center observations in the ordered list. The position of the two middle values are n/2 and (n/2) + 1. The Fi ...
Descriptive Statistics - University of Florida
Descriptive Statistics - University of Florida

... – If too cramped/narrow, break stems into two groups: low with leaves 0-4 and high with leaves 5-9 – When numbers have many digits, trim off right-most (less significant) digits. Leaves should always be a single digit. ...
< 1 ... 41 42 43 44 45 46 47 48 >

Categorical variable

In statistics, a categorical variable is a variable that can take on one of a limited, and usually fixed, number of possible values, thus assigning each individual to a particular group or ""category."" In computer science and some branches of mathematics, categorical variables are referred to as enumerations or enumerated types. Commonly (though not in this article), each of the possible values of a categorical variable is referred to as a level. The probability distribution associated with a random categorical variable is called a categorical distribution.Categorical data is the statistical data type consisting of categorical variables or of data that has been converted into that form, for example as grouped data. More specifically, categorical data may derive from either or both of observations made of qualitative data, where the observations are summarised as counts or cross tabulations, or of quantitative data, where observations might be directly observed counts of events happening or might be counts of values that occur within given intervals. Often, purely categorical data are summarised in the form of a contingency table. However, particularly when considering data analysis, it is common to use the term ""categorical data"" to apply to data sets that, while containing some categorical variables, may also contain non-categorical variables.A categorical variable that can take on exactly two values is termed a binary variable or dichotomous variable; an important special case is the Bernoulli variable. Categorical variables with more than two possible values are called polytomous variables; variables are often assumed to be polytomous unless otherwise specified. Discretization is treating continuous data as if it were categorical. Dichotomization is treating continuous data or polytomous variables as if they were binary variables. Regression analysis often treats category membership as a quantitative dummy variable.
  • studyres.com © 2025
  • DMCA
  • Privacy
  • Terms
  • Report