• 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
Slides 1-22 Estimation
Slides 1-22 Estimation

Methods of Presenting Data - Penn Arts and Sciences
Methods of Presenting Data - Penn Arts and Sciences

Chapter 10
Chapter 10

... Dependent Sample Examples • The same test is given to all students at the beginning and end of a course to measure learning (one pair of scores per person). • IQ tests are given to husband & wife pairs. • A medical treatment is given to patients matched for condition, age, sex, race, weight, and ot ...
2. Remember our assumptions for Hypothesis tests
2. Remember our assumptions for Hypothesis tests

Take-Home Test #3 v111213 The following chart is of batting
Take-Home Test #3 v111213 The following chart is of batting

Name: Date: ______ 1. In formulating hypotheses for a statistical test
Name: Date: ______ 1. In formulating hypotheses for a statistical test

H 0
H 0

HypothesisTesting2011
HypothesisTesting2011

... p–value in hypothesis testing The probability of observing a sample value as extreme as, or mote extreme than, the value observed, given that the null hypothesis is true. •If p-value H0 is rejected •If p-value>significance level => H0 is not rejected •Gives us also additional ...
lecture
lecture

Power of a test
Power of a test

Chapter 14 – Analysis of Variance (ANOVA)
Chapter 14 – Analysis of Variance (ANOVA)

Chapters8-9-10-F12
Chapters8-9-10-F12

Chapter 4 Statistical inferences
Chapter 4 Statistical inferences

... the population parameter is likely to occur within that range at a specified probability. • Specified probability is called the level of confidence. • States how much confidence we have that this interval contains the true population parameter. The confidence level is denoted by (1-α)×100% • Example ...
Chapter 9
Chapter 9

ECO383 Economics of Education In-Class Test – Sample Solutions ∗
ECO383 Economics of Education In-Class Test – Sample Solutions ∗

Chapter 9
Chapter 9

... When the population standard deviation (σ) is unknown, the sample standard deviation (s) is used in ...
Making Decisions and Considering the Consequences
Making Decisions and Considering the Consequences

AMS312.01 Lecture notes April 14, 2008 Prof. Wei Zhu
AMS312.01 Lecture notes April 14, 2008 Prof. Wei Zhu

1. The claim is that the proportion of women who use Internet
1. The claim is that the proportion of women who use Internet

... b) Based on his theory of genetics, Mendel expected that 25% of the offspring peas would be yellow. Given that the percentage of offspring yellow peas is not 25%, do the results contradict Mendel’s theory? Why or why not? The 95% confidence interval does not include 0.25, so this single experiment d ...
STATISTICS - SUMMARY - Michigan State University
STATISTICS - SUMMARY - Michigan State University

... Note we could have rejected null hypothesis at .001 level here. WHAT HAVE WE DONE? We have used probability theory to determine the likelihood of obtaining a contingency table with a Chi square of 13.67 or greater given that there is no relationship between gender and IMUSE. If there is no relations ...
Sample
Sample

Econ173_fa02FinalAnswers
Econ173_fa02FinalAnswers

... Do not reject the null hypothesis, the means are not different c. reject the null hypothesis, the means are not different d. Do not reject the null hypothesis, the mean of population 2 is greater. 38. If on the other hand, you do a one tailed test with H1: 1 > 2, and still obtain the same test sta ...
Using the TI-86 to Find the Sample Mean and Sample Standard
Using the TI-86 to Find the Sample Mean and Sample Standard

Clinical Chemistry Chapter 3
Clinical Chemistry Chapter 3

ENGG2430A-Homework 5
ENGG2430A-Homework 5

... (b) What can we assert with 98% confidence about the possible size of our error if we estimate the mean height of all college students to be 174.5 centimeters? Solution: By the previous part, we can assert with 98% confidence that the error |x̄ − µ| is no larger than zα/2 √sn = 2.27. This is again b ...
< 1 ... 222 223 224 225 226 227 228 229 230 ... 285 >

Misuse of statistics

Statistics are supposed to make something easier to understand but when used in a misleading fashion can trick the casual observer into believing something other than what the data shows. That is, a misuse of statistics occurs when a statistical argument asserts a falsehood. In some cases, the misuse may be accidental. In others, it is purposeful and for the gain of the perpetrator. When the statistical reason involved is false or misapplied, this constitutes a statistical fallacy.The false statistics trap can be quite damaging to the quest for knowledge. For example, in medical science, correcting a falsehood may take decades and cost lives.Misuses can be easy to fall into. Professional scientists, even mathematicians and professional statisticians, can be fooled by even some simple methods, even if they are careful to check everything. Scientists have been known to fool themselves with statistics due to lack of knowledge of probability theory and lack of standardization of their tests.
  • studyres.com © 2025
  • DMCA
  • Privacy
  • Terms
  • Report