Topic 4: Normal Model Flashcards

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1
Q

What is normal model?

A

A model used for data that is fairly symmetric and used to capture the general trend.

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2
Q

Why do we use normal model?

A
  • Normal model represents many natural phenomenon
  • Models data caused by different factors (Central Limit Theorem)
  • Defined by mean and SD (easy to use)
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3
Q

How many types of normal models are there? Describe them

A
  • Standard normal model: N(0,1)
  • General normal model: N(mean, SD^2)
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4
Q

When is normal model used?

A

A histogram that has quite a bell shape.

Diagnostics:
- Does the histogram look normal? (no long tails or many outliers)
- Do the proportions look right? (or does it fit into the 68/95/99.7% rule?)
- Does the quantile-quantile (QQ) plot look linear?
- Does the shapiro test have low value? (<0.05: not fit)

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5
Q

What commands are used to determine the area under the curve or the threshold of that area?

A

pnorm(x) (cumulative distribution function): used to calculate the area(%) of the area under the curve (lower tail)
pnorm(x); pnorm(x, lower.tail=F); pnorm(x,mean,SD)
x is the threshold

qnorm(y) (quantile function): determine the threshold of the area
qnorm(y,mean,SD)
y is the area/the percentile

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6
Q

How to rescale general normal model to standard normal model?

A

Calculate the standard units (Z= (data points - mean)/SD)

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7
Q

How is individual measurement different from exact value?

A

Individual measurement = exact value + chance error + bias

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8
Q

How can we estimate chance error?

A

Chance error happens because measured value turns out differently every time.
Chance error can be estimated by replicating the measurement to calculate the SD.

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9
Q

What is bias?

A

Bias is a systamic error that is in a constant amount added or subtracted from the measurement.

Bias cannot be estimated by replicating the measurement.

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10
Q

What does the area under the normal curve approximate?

A

The area under the normal curve approximates that section of the histogram.

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11
Q

What is reproducible research and why is it important?

A

Reproducible research is a research that makes data sets and software used available for verifying published findings and alternative analyse.

Without reproducible research, data versions and graphical summaries can change.

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