• 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
taxi problem - Ing-Stat
taxi problem - Ing-Stat

Sample Location Problems
Sample Location Problems

Chapter 7 Measuring of data
Chapter 7 Measuring of data

... The numeric codes assigned in nominal measurement do not convey quantitative information. If we classify males as 1 and females as 2, the numbers have no inherent meaning. The number 2 clearly does not mean “more than” 1. It would be perfectly acceptable to reverse the code and use 1 for females an ...
Sampling distributions
Sampling distributions

set2
set2

ANOVA & Regression
ANOVA & Regression

... statistically significant. You must always set a confidence level before determining if the p value is large enough to be statistically significant. Findings from small samples are unlikely to be significant unless there is a very strong relationship between two variables. ...
Statistics 13V NAME: Quiz 7 Last six digits of Student ID#: For
Statistics 13V NAME: Quiz 7 Last six digits of Student ID#: For

Math 1231—Fall 2012 Review Sheet for Exam #1 THIS IS NOT
Math 1231—Fall 2012 Review Sheet for Exam #1 THIS IS NOT

... The list below is intended to highlight the important topics that have been covered so far in the course. However, any problem or topic that has been covered during lecture, on homework, or in the reading is considered a fair question on the exam, with specific exceptions listed below. You will need ...
Illuminating Data
Illuminating Data

Matched pairs (“paired” or “dependent” samples) t-tests - BYU
Matched pairs (“paired” or “dependent” samples) t-tests - BYU

Week 1: Descriptive Statistics
Week 1: Descriptive Statistics

DM Chapter 16 Test Review
DM Chapter 16 Test Review

... a. How large a sample do they need if they want to estimate the true population proportion that failed within 5% with 99% confidence? n = ___________ b. What would the margin of error be with this sample size if they only required 95% confidence? ME = _______________ 13. Suppose President Obama’s st ...
Inferential statistics/review for exam 1
Inferential statistics/review for exam 1

Exam III 2008 solutions
Exam III 2008 solutions

Statistical Significance and Bivariate Tests
Statistical Significance and Bivariate Tests

... • The P-value of the test statistic, is the area of the sampling distribution from the sample result in the direction of the alternative hypothesis. • Interpretation: If the null hypothesis is correct, than the p-value is the probability of obtaining a sample that yielded your statistic, or a statis ...
written sources of data
written sources of data

... – There are few values, and few scores, occurring which have a similar frequency • Median: – There are many ordinal values ...
Quiz #1
Quiz #1

Document
Document

PPT
PPT

... • Conclusion: The test has provided evidence that the fertilizer caused the corn to grow more than if it had not been fertilized. The amount of actual increase was not large (1.36 inches over normal growth), but it was statistically significant. ...
22.nonexp4 - Illinois State University Department of Psychology
22.nonexp4 - Illinois State University Department of Psychology

... H0: mean of Group A = mean of Group B Alternative HA: mean of Group A ≠ mean of Group B  (Or more precisely: Group A > Group B) ...
Tue Jan 27 - Wharton Statistics
Tue Jan 27 - Wharton Statistics

Chapter 3 McGrew and Monroe
Chapter 3 McGrew and Monroe

transparency of financial time series.(Topic 1)
transparency of financial time series.(Topic 1)

Data Handling/Statistics - LSU Macromolecular Studies Group
Data Handling/Statistics - LSU Macromolecular Studies Group

PPT19
PPT19

... The value of F will vary from zero to large values. If it is close to zero, then the null hypothesis is likely. If the F value above is large, the null hypothesis is unlikely. ...
< 1 ... 206 207 208 209 210 211 212 213 214 ... 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