3 - Intro to Stats Flashcards

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1
Q

What does a small sample population mean?

A
  • Low level of precision
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2
Q

What words shouldn’t you use when making conclusions?

A

’ inaccurate, inexact, invalid ‘

Say results due to chance, bias or confounding variable

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3
Q

How would you find true or underlying value?

A
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4
Q

What is a hypothesis and how is it tested?

A

Hypothesis test - Make a statement about the probability of observed data at least as extreme as that observed if the stated hypothesis is true, allows us to decide whether to reject or not

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5
Q

How do you interpret p values for hypothesis testing?

A
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6
Q

What are the limitations with p values for hypothesis testing?

A
  1. p = 0.05 is arbitary, one could be 0.049 and other could be 0.051, not much difference but one significant and one not
  2. Statistically significant /= clinically important
  3. Statistical significance depends on sample size
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7
Q

What is a null hypothesis and how do you interpret it?

A

Hypothesis assuming there is no significant difference between two groups

  • p < 0.05 strongly suggests hypothesis is false
  • p > 0.05 data is consistent with null hypothesis but not proven
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8
Q

What are 95% CI?

A

Measure of precision of observed values

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9
Q

Where does observed values lie in stats tests?

A

ALWAYS LIE WITHIN 95% CI, IN THE MIDDLE

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10
Q

What are the values inclusive of 95% CI said to be?

A

Consistent with the data

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11
Q

What makes the 95% CI wider?

A
  • Smaller sample size
  • Greater variation in population values
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12
Q

What is the value of the null hypothesis if true?

A
  • 0 if looking at difference/reduction
  • 1 if looking at ratios
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