What is a Hypothesis?mba. 2013. 2. 14.آ  What is a Hypothesis? A hypothesis is a claim...

download What is a Hypothesis?mba. 2013. 2. 14.آ  What is a Hypothesis? A hypothesis is a claim (assumption)

of 40

  • date post

    21-Feb-2021
  • Category

    Documents

  • view

    0
  • download

    0

Embed Size (px)

Transcript of What is a Hypothesis?mba. 2013. 2. 14.آ  What is a Hypothesis? A hypothesis is a claim...

  • What is a Hypothesis?

     A hypothesis is a claim (assumption) about a population parameter:

    population mean

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 9-1

     population mean

     population proportion

    Example: The mean monthly cell phone bill in this city is μ = $42

    Example: The proportion of adults in this city with cell phones is π = 0.68

  • The Null Hypothesis, H0

     States the claim or assertion to be tested

    Example: The average number of TV sets in

    U.S. Homes is equal to three ( )3μ:H0 

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 9-2

     Is always about a population parameter, not about a sample statistic

    3μ:H0  3X:H0 

  • The Null Hypothesis, H0

     Begin with the assumption that the null hypothesis is true

     Similar to the notion of innocent until proven guilty

    (continued)

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 9-3

    proven guilty

     Refers to the status quo or historical value

     Always contains “=” , “≤” or “” sign

     May or may not be rejected

  • The Alternative Hypothesis, H1

     Is the opposite of the null hypothesis

     e.g., The average number of TV sets in U.S. homes is not equal to 3 ( H1: μ ≠ 3 )

     Challenges the status quo

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 9-4

    Challenges the status quo

     Never contains the “=” , “≤” or “” sign

     May or may not be proven

     Is generally the hypothesis that the researcher is trying to prove

  • The Hypothesis Testing Process

     Claim: The population mean age is 50.  H0: μ = 50, H1: μ ≠ 50

     Sample the population and find sample mean.

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 9-5

    Population

    Sample

  • The Hypothesis Testing Process

    Sampling Distribution of X

    (continued)

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 9-6

    μ = 50 If H0 is true

    If it is unlikely that you would get a sample mean of this value ...

    ... then you reject the null hypothesis

    that μ = 50.

    20

    ... When in fact this were the population mean…

    X

  • The Test Statistic and Critical Values

     If the sample mean is close to the assumed population mean, the null hypothesis is not rejected.

     If the sample mean is far from the assumed

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 9-7

     If the sample mean is far from the assumed population mean, the null hypothesis is rejected.

     How far is “far enough” to reject H0?

     The critical value of a test statistic creates a “line in the sand” for decision making -- it answers the question of how far is far enough.

  • The Test Statistic and Critical Values

    Sampling Distribution of the test statistic

    Region of Rejection

    Region of Rejection

    Region of

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 9-8

    Critical Values

    “Too Far Away” From Mean of Sampling Distribution

    Rejection Region of

    Non-Rejection

  • Possible Errors in Hypothesis Test Decision Making

     Type I Error

     Reject a true null hypothesis

     Considered a serious type of error

     The probability of a Type I Error is 

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 9-9

     Called level of significance of the test

     Set by researcher in advance

     Type II Error

     Failure to reject false null hypothesis

     The probability of a Type II Error is β

  • Possible Errors in Hypothesis Test Decision Making

    Possible Hypothesis Test Outcomes

    Actual Situation

    (continued)

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 9-10

    Decision H0 True H0 False

    Do Not Reject H0

    No Error

    Probability 1 - α

    Type II Error

    Probability β

    Reject H0 Type I Error

    Probability α

    No Error

    Probability 1 - β

  • Possible Errors in Hypothesis Test Decision Making

     The confidence coefficient (1-α) is the probability of not rejecting H0 when it is true.

     The confidence level of a hypothesis test is

    (continued)

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 9-11

     The confidence level of a hypothesis test is (1-α)*100%.

     The power of a statistical test (1-β) is the probability of rejecting H0 when it is false.

  • Type I & II Error Relationship

     Type I and Type II errors cannot happen at the same time

     A Type I error can only occur if H0 is true

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 9-12

     A Type I error can only occur if H0 is true

     A Type II error can only occur if H0 is false

    If Type I error probability (  ) , then

    Type II error probability ( β )

  • Factors Affecting Type II Error

     All else equal,

     β when the difference between

    hypothesized parameter and its true value

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 9-13

     β when 

     β when σ

     β when n

  • Level of Significance and the Rejection Region

    Level of significance = aH0: μ = 3

    H1: μ ≠ 3

    /2a/2a

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 9-14

    This is a two-tail test because there is a rejection region in both tails

    Critical values

    Rejection Region

    0

  • 2 Test of Independence

     Similar to the 2 test for equality of more than two proportions, but extends the concept to contingency tables with r rows and c columns

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 12-15

    H0: The two categorical variables are independent

    (i.e., there is no relationship between them)

    H1: The two categorical variables are dependent

    (i.e., there is a relationship between them)

  • Wilcoxon Rank-Sum Test: Hypothesis and Decision Rule

    H : M = M H : M  MH : M  M Two-Tail Test Left-Tail Test Right-Tail Test

    M1 = median of population 1; M2 = median of population 2 Test statistic = T1 (Sum of ranks from smaller sample)

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 12-16

    H0: M1 = M2 H1: M1  M2

    H0: M1  M2 H1: M1 > M2

    H0: M1  M2 H1: M1 < M2

    Reject

    T1L T1U

    RejectDo Not Reject

    Reject

    T1L

    Do Not Reject

    T1U

    RejectDo Not Reject

    Reject H0 if T1 ≤ T1L or if T1 ≥ T1U

    Reject H0 if T1 ≤ T1L Reject H0 if T1 ≥ T1U

  • Sample data are collected on the capacity rates

    (% of capacity) for two factories.

    Are the median operating rates for two factories

    the same?

    Wilcoxon Rank-Sum Test: Small Sample Example

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 12-17

    the same?

     For factory A, the rates are 71, 82, 77, 94, 88

     For factory B, the rates are 85, 82, 92, 97

    Test for equality of the population medians

    at the 0.05 significance level

  • Wilcoxon Rank-Sum Test: Small Sample Example

    Capacity Rank

    Factory A Factory B Factory A Factory B

    71 1

    77 2

    82 3.5Tie in 3rd

    Ranked Capacit

    y values:

    (continued)

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 12-18

    82 3.5

    82 3.5

    85 5

    88 6

    92 7

    94 8

    97 9

    Rank Sums: 20.5 24.5

    Tie in 3rd

    and 4th

    places

  • Wilcoxon Signed Ranks Test

     A nonparametric test for two related populations

     Steps:

    1. For each of n sample items, compute the difference, Di, between two measurements

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 12-19

    Di, between two measurements

    2. Ignore + and – signs and find the absolute values, |Di|

    3. Omit zero differences, so sample size is n’

    4. Assign ranks Ri from 1 to n’ (give average rank to

    ties)

    5. Reassign + and – signs to the ranks Ri 6. Compute the Wilcoxon test statistic W as the sum of

    the positive ranks

  • Wilcoxon Signed Ranks Test Statistic

     The Wilcoxon signed ranks test statistic is the sum of the positive ranks:

      n'

    )(RW

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 12-20

     For small samples (n’ < 20), use Table E.9 for

    the critical value of W

     

     1i

    )( iRW

  • Wilcoxon Signed Ranks Test Statistic

     For samples of n’ > 20, W is approximately

    normally distributed with

    1)(n'n' 

    Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc.. Chap 12-21

    24

    1)1)(2n'(n'n' σ

    4