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# Statistics! - PowerPoint PPT Presentation

Statistics!. Today. Check in How is that proposal coming along…? Finish up material from Tuesday Statistics. Statistics. Purpose for today and Tuesday Familiarize you with statistical terms and concepts Help you get a general sense of statistics What are they? Why do we use them?

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## PowerPoint Slideshow about 'Statistics!' - daw

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Presentation Transcript

### Statistics!

• Check in

• How is that proposal coming along…?

• Finish up material from Tuesday

• Statistics

• Purpose for today and Tuesday

• Familiarize you with statistical terms and concepts

• What are they?

• Why do we use them?

• What are some basic statistics?

• Statistics are numbers that describe a sample

• Parameters are numbers that describe a population

• We use them to describe our variables

• Descriptive statistics

• We use them to make inferences from samples to populations

• Inferential statistics

• This is why sampling and bias are so very important

• Frequencies

• Remember: variables are divided into categories

• Frequencies tell us how many are in each type of category

• Frequencies can refer to the raw number, or the percent

• Nominal

• Ordinal

• Interval

• Ratio

• “named” variables

• Can be represented with numbers but have no numerical qualities

• There is no rank order

• E.g. Red, blue, green cars

• Male/female gender

green

blue

red

• Variables that have “order”

• We assign them a rank, and may use numbers

• We don’t actually know how much the ranks differ

• Some of the time, most of the time, all of the time

3

2

1

• We should not manipulate ordinal variables numerically

• Because we don’t know if the categories are exact

• But in practice ordinal variables are numerically manipulated all the time

• Interval data is rank ordered

• We know that the space from one to the next is “equal”

• E.g. temperature

• But interval data has “no true zero”

• There can’t be a true absence of the thing being measured

• Like temperature, zero is “arbitrary”

• We decide what zero is

“heat”

Less than 0

Even more less than 0

“0”

1

2

3

4

• Like interval data

• It is ordered

• We know that the space from one rating to the next is “equal”

• It has a “true zero”

• There CAN be an absence of it

• E.g. length, weight

• You can have “zero” weight

“Weight”

0

1

2

3

4

Useful terms

• Univariate—referring to a single variable

• Bivariate—two variables

• Multivariate—more than two variables

• Proportion—a percent