• Study Resource
  • Explore Categories
    • 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
Stats Review Lecture 3 - Random Variables 08.29.12
Stats Review Lecture 3 - Random Variables 08.29.12

Chapter 1: Statistics
Chapter 1: Statistics

... Example: A machine used to fill 5-gallon buckets of driveway sealer has standard deviation 2.5 ounces. A random sample of 24 buckets showed a standard deviation of 2.9 ounces. Is there any evidence to suggest an increase in variability at the 0.05 level of significance? Assume the amount of drivewa ...
Populations and Samples Chapter 8
Populations and Samples Chapter 8

Testing Differences between Means continued
Testing Differences between Means continued

Quiz 5 Key
Quiz 5 Key

Descriptive Biostatistics
Descriptive Biostatistics

1 Random Variables
1 Random Variables

Lesson 8.1 Estimation µ when σ is Known Notes
Lesson 8.1 Estimation µ when σ is Known Notes

... 1. We have a simple random sample of size n drawn from a population of x values. 2. The value of σ, the population standard deviation of x, is known 3. If the x distribution is normal, then our methods work for any sample size n. 4. If x has an unknown distribution then we require a sample size n ≥ ...
notes on Measures of Dispersion, Symmetry and
notes on Measures of Dispersion, Symmetry and

Chapter 3: Single Factor Experiments with No Restrictions on
Chapter 3: Single Factor Experiments with No Restrictions on

Survey Tabulation: Stats 101
Survey Tabulation: Stats 101

... the mean (average), median, standard deviation and standard error are often included on tables for analysis purposes. For example, it might be helpful to show the mean of a rating scale question and other numeric fields (i.e., age or income values). These measures summarize the key results in a few ...
AP Statistics Chapter 11 - William H. Peacock, LCDR USN
AP Statistics Chapter 11 - William H. Peacock, LCDR USN

... elementary school. Though there is a 25 MPH SCHOOL ZONE sign nearby, most drivers seem to go much faster than that, even when the warning sign flashes. The students randomly selected 20 flashing zone times during the school year, noted the speeds of the cars passing the school during the flashing zo ...
Lecture 14
Lecture 14

... There was some relationship between tests scores and the type of community in which the parents lived. For example, big-city children averaged 26 points on the tests, and the SD was 10 points. Rural children average 25 points with the same SD. Can the difference be explained as chance variation? Ass ...
Document
Document

The Central Theorem for Sums
The Central Theorem for Sums

Lecture 3 - UC Davis Plant Sciences
Lecture 3 - UC Davis Plant Sciences

Just My Cup of t (test)
Just My Cup of t (test)

... In science, researchers are often looking to see if experimental group data are significantly different from control group data. (If the data are significantly different, the researchers may propose that their treatment, the independent variable, within the experimental group caused the observed dif ...
document
document

Normalizing data.
Normalizing data.

... 1 Overview We often want to compare scores or sets of scores obtained on different scales. For example, how do we compare a score of 85 in a cooking contest with a score of 100 on an I.Q. test? In order to do so, we need to “eliminate” the unit of measurement, this operation is called to normalize t ...
Document
Document

Hatfield.Topic 10
Hatfield.Topic 10

Chapter 23 Powerpoint dv01_23
Chapter 23 Powerpoint dv01_23

Section 18: Inferences about Means (σ unknown, sample “small
Section 18: Inferences about Means (σ unknown, sample “small

Psychology 101
Psychology 101

Business Statistics for Managerial Decision
Business Statistics for Managerial Decision

< 1 ... 78 79 80 81 82 83 84 85 86 ... 114 >

Degrees of freedom (statistics)

In statistics, the number of degrees of freedom is the number of values in the final calculation of a statistic that are free to vary.The number of independent ways by which a dynamic system can move, without violating any constraint imposed on it, is called number of degrees of freedom. In other words, the number of degrees of freedom can be defined as the minimum number of independent coordinates that can specify the position of the system completely.Estimates of statistical parameters can be based upon different amounts of information or data. The number of independent pieces of information that go into the estimate of a parameter are called the degrees of freedom. In general, the degrees of freedom of an estimate of a parameter are equal to the number of independent scores that go into the estimate minus the number of parameters used as intermediate steps in the estimation of the parameter itself (i.e. the sample variance has N-1 degrees of freedom, since it is computed from N random scores minus the only 1 parameter estimated as intermediate step, which is the sample mean).Mathematically, degrees of freedom is the number of dimensions of the domain of a random vector, or essentially the number of ""free"" components (how many components need to be known before the vector is fully determined).The term is most often used in the context of linear models (linear regression, analysis of variance), where certain random vectors are constrained to lie in linear subspaces, and the number of degrees of freedom is the dimension of the subspace. The degrees of freedom are also commonly associated with the squared lengths (or ""sum of squares"" of the coordinates) of such vectors, and the parameters of chi-squared and other distributions that arise in associated statistical testing problems.While introductory textbooks may introduce degrees of freedom as distribution parameters or through hypothesis testing, it is the underlying geometry that defines degrees of freedom, and is critical to a proper understanding of the concept. Walker (1940) has stated this succinctly as ""the number of observations minus the number of necessary relations among these observations.""
  • studyres.com © 2026
  • DMCA
  • Privacy
  • Terms
  • Report