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Hypothesis Testing & p-value
Dr. Athar Khan
MBBS, MCPS, DPH, MBA, DCPS-HPE, DCPS-HCSM,
PGD-Statistics, BA, MA, PhD Scholar
Associate Professor
Department of Community Medicine
Liaquat College of Medicine & Dentistry
matharm@yahoo.com
CHAPTER # of BCQ’s #EMQ’s
General epidemiology and screening 9 1
Demography and population dynamics 7 1
Biostatistics 5 1
TOTAL MARKS 21 3
HYPOTHESIS
• Any statement about a population is termed as
hypothesis. OR
• A hypothesis is an educated guess or proposition
that attempts to explain a set of facts or natural
phenomenon. OR
• A hypothesis is a proposed explanation for a
phenomenon. 
HYPOTHESIS
• Null Hypothesis(Ho) : There is NO difference or
association or relationship between the abdominal
and vaginal hysterectomy with respect to post
operative complications
• Alternate Hypothesis (Ha/H1) : There is a difference or
association or relationship between the abdominal
and vaginal hysterectomy with respect to post
operative complications
ALTERNATIVE HYPOTHESIS
• Alternative hypothesis is generally the research
question or researcher hypothesis.
• Null hypothesis is usually against the claim of the
researcher and every researcher would like to reject
this hypothesis
ALTERNATIVE HYPOTHESIS
• There is difference in complications between AH
and VH (Two Tailed/Two sided)
• VH has less complications than AH (One
Tailed/One sided)
• VH has more complications than AH (One
Tailed/One sided)
ALTERNATIVE HYPOTHESIS
• Our final decision is based on to:
– Reject the Null Hypothesis
– Fail to reject (accept) the Null Hypothesis
ONESIDEDorONETAILED
TWOSIDED
TWOTAILED
Rejection Area
Non-Rejection
Area
SITUATION ONE:
REJECT THE NULL HYPOTHESIS
TRUE SITUATION NULL HYPOTHESIS DECISION
REJECT Ho REJECTED RIGHT √
REJECT Ho NOT REJECTED WRONG
SITUATION TWO
FAIL TO REJECT THE NULL HYPOTHESIS
TRUE SITUATION NULL HYPOTHESIS DECISION
FAIL TO REJECT Ho NOT REJECTED RIGHT √
FAIL TO REJECT Ho REJECTED WRONG
• We make decision in research on the basis of
available evidence.
• Are we 100% sure?
• Is there a chance of error in our decision?
• Maximum 5% (0.05) is reasonable in making decision
about Ho. Sometimes 10% (0.1) and more accurate
1% (0.01) may be considered.
LEVEL OF SIGNIFICANCE OR Alpha 
• The chance of error which is set before starting
experiment and is fixed at 1%, 5%,10% is known as
level of significance of Alpha 
• 0.01 probability = 1%
• 0.05 probability = 5%
• 0.1 probability = 10%
MOST COMMON
CONFIDENCE LEVEL
Confidence Level = 1 – α
If α = 0.05
Confidence Level = 1 – α
Confidence Level = 1 – 0.05
Confidence Level = 0.95 or 95%
If α = 0.01 and α = 0.1
MOST COMMON
ONESIDEDorONETAILED
TWOSIDED
TWOTAILED
Significance Level
Confidence Level
TYPES OF ERRORS
DESIRE OF RESEARCHER IS TO REJECT Ho
TRUE SITUATION
DECISION Ho TRUE Ho FALSE
REJECT Ho Type I error or α error CORRECT
Fail to reject (accept) Ho CORRECT Type II error or β error
Type I error - α error (RTA):
Rejecting Ho when actually it is true.
Type II error - β error (AFB):
Fail to reject Ho when actually it is false.
What is Power of a Test?
– Power = P(reject null | null is false)
– It is the probability of rejecting Ho when Ho is indeed
false.
Power = 1 – β
If β = 20 then 1 – β = 80% so that we would have
rejected the false Ho about 80% of the time.
Hints for BCQ’s
– Alpha error s serious than Beta error
– Alpha error 5%(0.05) or less is acceptable
– Beta error 20%(0.20) or less is acceptable
– Power of the study 80%(0.80) or more is acceptable
P VALUE
DEFINITION
• Probability of committing Type I error OR
• Probability of rejecting Ho when actually it is true
OR
• Probability of falsely rejecting Ho OR
• Probability of getting a result by chance
• P-Values range from 0 to 1
P value and Significance level
• Level of significance is set before starting the
experiment and is fixed at 1%, 5%, 10% but P value
is calculated after completing the experiment and it
is not fixed.
• If p value is less than will reject Ho and if it is
more than  we will not reject Ho.
Interpreting p value
P value Inter pretation
P > 0.05 Result is not statistically significant
P < 0.05
Result is statistically significant *
<5% of committing Type I error
95% confident that real difference or not due to
chance
P < 0.01 Result is highly statistically significant **
P < 0.001
Result is very highly statistically significant ***
MOST COMMON

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Hypothesis testing

  • 1. Hypothesis Testing & p-value Dr. Athar Khan MBBS, MCPS, DPH, MBA, DCPS-HPE, DCPS-HCSM, PGD-Statistics, BA, MA, PhD Scholar Associate Professor Department of Community Medicine Liaquat College of Medicine & Dentistry matharm@yahoo.com
  • 2. CHAPTER # of BCQ’s #EMQ’s General epidemiology and screening 9 1 Demography and population dynamics 7 1 Biostatistics 5 1 TOTAL MARKS 21 3
  • 3. HYPOTHESIS • Any statement about a population is termed as hypothesis. OR • A hypothesis is an educated guess or proposition that attempts to explain a set of facts or natural phenomenon. OR • A hypothesis is a proposed explanation for a phenomenon. 
  • 4. HYPOTHESIS • Null Hypothesis(Ho) : There is NO difference or association or relationship between the abdominal and vaginal hysterectomy with respect to post operative complications • Alternate Hypothesis (Ha/H1) : There is a difference or association or relationship between the abdominal and vaginal hysterectomy with respect to post operative complications
  • 5. ALTERNATIVE HYPOTHESIS • Alternative hypothesis is generally the research question or researcher hypothesis. • Null hypothesis is usually against the claim of the researcher and every researcher would like to reject this hypothesis
  • 6. ALTERNATIVE HYPOTHESIS • There is difference in complications between AH and VH (Two Tailed/Two sided) • VH has less complications than AH (One Tailed/One sided) • VH has more complications than AH (One Tailed/One sided)
  • 7. ALTERNATIVE HYPOTHESIS • Our final decision is based on to: – Reject the Null Hypothesis – Fail to reject (accept) the Null Hypothesis
  • 9. SITUATION ONE: REJECT THE NULL HYPOTHESIS TRUE SITUATION NULL HYPOTHESIS DECISION REJECT Ho REJECTED RIGHT √ REJECT Ho NOT REJECTED WRONG
  • 10. SITUATION TWO FAIL TO REJECT THE NULL HYPOTHESIS TRUE SITUATION NULL HYPOTHESIS DECISION FAIL TO REJECT Ho NOT REJECTED RIGHT √ FAIL TO REJECT Ho REJECTED WRONG
  • 11. • We make decision in research on the basis of available evidence. • Are we 100% sure? • Is there a chance of error in our decision? • Maximum 5% (0.05) is reasonable in making decision about Ho. Sometimes 10% (0.1) and more accurate 1% (0.01) may be considered.
  • 12. LEVEL OF SIGNIFICANCE OR Alpha  • The chance of error which is set before starting experiment and is fixed at 1%, 5%,10% is known as level of significance of Alpha  • 0.01 probability = 1% • 0.05 probability = 5% • 0.1 probability = 10% MOST COMMON
  • 13. CONFIDENCE LEVEL Confidence Level = 1 – α If α = 0.05 Confidence Level = 1 – α Confidence Level = 1 – 0.05 Confidence Level = 0.95 or 95% If α = 0.01 and α = 0.1 MOST COMMON
  • 15. TYPES OF ERRORS DESIRE OF RESEARCHER IS TO REJECT Ho TRUE SITUATION DECISION Ho TRUE Ho FALSE REJECT Ho Type I error or α error CORRECT Fail to reject (accept) Ho CORRECT Type II error or β error Type I error - α error (RTA): Rejecting Ho when actually it is true. Type II error - β error (AFB): Fail to reject Ho when actually it is false.
  • 16. What is Power of a Test? – Power = P(reject null | null is false) – It is the probability of rejecting Ho when Ho is indeed false. Power = 1 – β If β = 20 then 1 – β = 80% so that we would have rejected the false Ho about 80% of the time.
  • 17. Hints for BCQ’s – Alpha error s serious than Beta error – Alpha error 5%(0.05) or less is acceptable – Beta error 20%(0.20) or less is acceptable – Power of the study 80%(0.80) or more is acceptable
  • 19. DEFINITION • Probability of committing Type I error OR • Probability of rejecting Ho when actually it is true OR • Probability of falsely rejecting Ho OR • Probability of getting a result by chance • P-Values range from 0 to 1
  • 20. P value and Significance level • Level of significance is set before starting the experiment and is fixed at 1%, 5%, 10% but P value is calculated after completing the experiment and it is not fixed. • If p value is less than will reject Ho and if it is more than  we will not reject Ho.
  • 21. Interpreting p value P value Inter pretation P > 0.05 Result is not statistically significant P < 0.05 Result is statistically significant * <5% of committing Type I error 95% confident that real difference or not due to chance P < 0.01 Result is highly statistically significant ** P < 0.001 Result is very highly statistically significant *** MOST COMMON