Normal Distribution Flashcards

(16 cards)

1
Q

Where are the points of inflection on a normal distribution curve?

A

Points of inflection are one standard deviation away from the mean

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2
Q

How much data lies within each standard deviation of the mean?

A

68% within 1 se of the mean
95% within 2 se of the mean
99.7% within 3 se of the mean

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3
Q

What is the difference between the data set of normal and binomial distribution?

A

Normal distribution is continuous whereas binomial is discrete

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4
Q

Where is the probability of a group of data on the normal distribution curve?

A

The area under the curve

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5
Q

What is the format was writing out that a variable is normally distributed?

A

X - N(Mean , se2)

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6
Q

How do you find IQR of normal distribution?

A

Find which value gives 0.75 probability and which gives 0.25
Find the difference between the two values

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7
Q

How to do inverse normal distribution?

A

Enter the probability into the calculator and find the value for which it corresponds to

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8
Q

What is the formula for standard normal distribution?

A

Z = X - Mean / se

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9
Q

What is the relationship between mean and median in normal distribution?

A

They are equal

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10
Q

What is the format of standard normal distribution?

A

Z - N(0 , 1)

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11
Q

Why is standard normal distribution have mean of 0 and se of 1?

A

Mean = 0 because mean is subtracted from every value
se = 1 because standard deviation is divided from every value

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12
Q

What is another way of writing out standard normal distribution?

A

Phi ( a ) = P( Z < a )

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13
Q

How do you approximate binomial distribution with normal distribution?

A

X - B(n , p)
Mean = n * p
Se = Sqrt(n * p *(1 - p))

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14
Q

What is the conditions for binomial distribution to be approximated with normal distribution?

A

‘n’ is large and ‘p’ is close to 0.5

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15
Q

Why does continuity correction need to be used?

A

Binomial is discrete whereas normal is continuous

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16
Q

How does each binomial inequality change to be normally distributed?

A

𝑃 (𝑋 ≀ π‘₯) —> 𝑃 (π‘Œ ≀ π‘₯ + 0.5)
𝑃 (𝑋 < π‘₯) —> 𝑃 (π‘Œ < π‘₯ - 0.5)
𝑃 (𝑋 β‰₯ π‘₯) —> 𝑃 (π‘Œ β‰₯ π‘₯ βˆ’ 0.5)
𝑃 (𝑋 > π‘₯) —> 𝑃 (π‘Œ > π‘₯ + 0.5)
𝑃 (𝑋 = π‘₯) —> 𝑃 (π‘₯ βˆ’ 0.5 < π‘Œ < π‘₯ + 0.5)