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Presentation 2
 

Presentation 2

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    Presentation 2 Presentation 2 Presentation Transcript

    • RAMESH DEBUR Hypothesis testing
    • The Way Back
      • Formulate a research Question
      • Develop a research Methodology
      • Collected Data
      • Sorted Data
    • The Way Forward
      • Introduction
      • GENERATE A HYPOTHESIS
        • NULL HYPOTHESIS
        • ALTERNATIVE HYPOTHESIS
      • Significance
        • The p Value
      • Errors
        • TYPE 1
        • TYPE 2
      • ACCEPT OR REJECT HYPOTHESIS
      • INFERENCE & PRESENTATION OF THE DATA
    • Hypothesis Testing
      • Scientific Hypothesis testing – A Deductive method of accepting or rejecting a hypothetical statement
    • Definition
      • A hypothesis consists either of a suggested explanation for a phenomenon
      • Eg: Gastric Juices produces Hunger
      • or
      • A reasoned proposal suggesting a possible correlation between multiple phenomena
      • Eg: People who smoke more cigarettes are at a higher risk of developing lung cancer
    • Therefore…..
      • Hypothesis testing implies either accepting or rejecting a certain statement.
      • Generating a Hypothesis
        • In Scientific Research the hypothesis is an offshoot of the research question
        • Eg: Do people who smoke more cigarettes increase their risk of developing Lung Cancer
    • The Logic of Hypothesis Testing
      • All hypothesis are false until proven true
      • The farther away from falsification the truer is the hypothesis
      • A Hypothesis is NEVER a Fact. We accept a hypothesis as true until it is falsified
      • Eg:
        • Columbus wants to discover a route to India
        • Columbus Discovers America
        • Every body he sees are called Indian – Hypothesis
        • Later learns they are not Indian – Hypothesis falsified
    • The NULL Hypothesis
      • The exact opposite of the perceived effect or change
      • Eg:
        • Gastric Juices DOES NOT cause Hunger
        • Smoking DOES NOT Increase the risk of Developing Lung Cancer
    • The Alternate Hypothesis
      • The Exact opposite of the NULL Hypothesis
      • Called alternate because the falsification is the primary logic of hypothesis testing
        • Gastric Juices DOES NOT cause Hunger
        • Smoking DOES NOT Increase the risk of Developing Lung Cancer
      • Easier to Falsify things than prove facts?????
    • Disproving Null Vs Proving the Alternate Null Alternate
    • THE NEXT QUESTION
      • WHEN DO WE REJECT THE NULL HYPOTHESIS
      • ANSWER : WHEN THE CHANCES OF IT BEING TRUE ARE VERY SLIM ( NON SIGNIFICANT)
      • PROBABILITY TESTING
    • Probability (prob·a·bil·i·ty)
      • Similar to Chance:
      • Derived from the Noun Probable
      • What is a probability :
      • The chance of a event occurring at any given time
      • The likelihood of an event having a particular outcome
      • Eg: Flipping a coin
      • All probability is between 0 and 1
    • Flip a coin
      • Likelihood of getting only 1 head in
        • 1 flip = 0.5
        • 2 flips = 0.34
        • 4flips = 0.24
        • 10 = 0.01
        • 100=0.00001
      • Likelihood of getting atleast 1 head in
        • 1 flip = 0.5
        • 2 flips = 0.66
        • 4flips = 0.76
        • 10 = 0.99
        • 100=0.999999
    • Probability as related to hypothesis testing
      • The p value
      • The likelihood that the data collected is equal to or more extreme than the null hypothesis
        • (logic: The Null hypothesis is the extreme value of an experiment)
      • Alternatively: The probability that the expected outcome occurred purely by chance
    • Significance - Definition
      • The significance level of a test is the probability that the test statistic will reject the null hypothesis when the [hypothesis] is true .
    • IN REAL TERMS
      • Get Test statistic (outcome of research )
      • Null hypothesis – test statistic
      • if > chance : accept test and reject null
      • If ≤ chance : reject test
      • Generally the significance is kept at 0.05 or 1 chance in 100 or 0.001( 1 in 1000)
    • Errors of Hypothesis testing α is also called as the significance value and is determined by the investigator Stastical Decision True state of the Null Hypothesis True H O False H O Reject H O Type 1 ( α ) Correct Do Not Reject H O Correct Type II ( β )
      • A type 1 error is considered much more serious than a type 2 error
      • Why? EG. A new drug is introduced into the market which can potentially cure hypertension but can also cause sudden death. Evaluate the chances of sudden death by the drug
      Statistical Decision True state of the Null Hypothesis True H O NO Death False H O Death Reject H O Type 1 ( α ) (Accept drug) Correct (Reject drug) Do Not Reject H O Correct (Accept Drug) Type II ( β ) (Reject Drug)