Statistics Chapter 1

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# Statistics Chapter 1 - PowerPoint PPT Presentation

Statistics Chapter 1. Lessons 1.1 – 1.3 Instructor: Mrs. Carroll. 1.1 Intro to Statistics. Statistics : the science of collecting, organizing, analyzing and interpreting data in order to make decisions

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## Statistics Chapter 1

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### Statistics Chapter 1

Lessons 1.1 – 1.3

Instructor: Mrs. Carroll

1.1 Intro to Statistics
• Statistics: the science of collecting, organizing, analyzing and interpreting data in order to make decisions
• Data - information coming from observations, counts, measurements or responses. The singular form is datum.
Data Sets
• Population: the collection of all outcomes, responses, measurements or counts that are of interest
• Sample: a subset of a population
• **it is usually impractical to obtain all of the data. In most studies, information must be obtained from a sample
Population or Sample
• Find the population and sample in each example:
• 1) 50 Mill Creek HS seniors were surveyed to find out what song they wanted for their senior song.
• 2) 2000 Republicans were polled to predict the outcome of the Republican presidential primary.
Results of Data Collection
• Parameter: a numerical description of a population characteristic
• Statistic: a numerical description of a sample characteristic
• Memory Tip: Think p for p, s for s.
Parameter or Statistic?
• 1) Of the 70 American Women surveyed, 35 said they prefer The Voice to American Idol. According to this survey, 50% of American Women prefer The Voice to American Idol.
• 2) The average professor salary at Orange Coast Community College is \$45,000.
Branches of Statistics
• Descriptive Statistics: a branch of statistics that involves the organization, summarization and displaying of data.
• Inferential Statistics: branch of statistics that involves using a sample to draw conclusions about a population. A basic tool in the study of inferential statistics is probability.
Quantitative/Qualitative Data Types
• Watch out for data that looks quantitative but really isn’t! - These have no real numeric value and no meaningful order.
• Examples:
• Social security numbers
• Phone numbers
• ID #s
Quantitative/Qualitative Data Types
• What type of data is it?
• Grade point average
• Jersey Numbers of Lacrosse Players
• Hair Color
• Number of Siblings
• Student ID Number
• SAT Score
• Weight in pounds
• Movie Rating (G, PG, PG-13, R)
• Temperature in Degrees F
• Finishing place in Track event (1st, 2nd, 3rd, etc.)
Classify Data by Level - Ratio

Ratio Level - __________________ data.

Categorize, put in order, find meaningful differences, AND find ratios. Also must have a true zero. Like average rainfall. Zero rainfall means NO rain fell. 20 inches is twice as much rain as 10 inches.

Key Questions:

1)Does zero mean “none”?

• Does “twice as much” or “twice as many” make sense?

Yes to both means ratio level.

Examples: rainfall, money

Can you think of data that is ratio level?

Classify Data by Level - Interval

Interval Level - __________________ data.

Categorize, put in order, AND find meaningful differences between values. Like average temperature.

The key here is that you must be able to subtract the values to show a real difference – like, “Today was ten degrees hotter than yesterday.”

Examples: temperature, dates

Classify Data by Level - Ordinal

Ordinal Level - __________________ OR _______________ data.

Categorize AND put in order, like good, better, and best product ratings.

How else do you categorize with an order?

Classify Data by Level - Nominal

Nominal Level - __________________ data.

Categorizes things – like genres of music.

How else do you categorize things or people?

Classify – Data Level
• Nominal, Ordinal, Interval or Ratio
• 1) Is it qualitative or quantitative?

Nominal or Ordinal Ordinal, Interval, or Ratio

Classify – Data Level
• Qualitative: Nominal or Ordinal
• Can you meaningfully order it?

No Yes

Nominal Ordinal

Classify – Data Level
• Quantitative Data : Ordinal, Interval or Ratio
• 1) Does twice as much have meaning?

No Yes

Ordinal or IntervalRatio

• Meaningful numeric differences?

No Yes

OrdinalInterval

Sampling
• Sampling is a count or measure of a part of the population. Sampling produces statistics.
• The difference between a statistic and a parameter is that a statistic is obtained from a part of the population (sample), while a parameter is obtained by measuring the entire population.
Sampling TechniquesSimple Random
• Every member of the population has an equal chance of being selected
Sampling TechniquesStratified Random
• Population is separated into groups (strata) – like age groups, gender, classes, etc.
• A random sample is then selected from each strata.
Sampling TechniquesCluster
• Population is separated into groups – like age groups, gender, classes, etc.
• One or more groups is selected and ALL of the members of those groups are selected.
Sampling TechniquesSystematic
• A system (or rule) is used to select the members of the sample.
• EX: every 100th customer, the first person listed on each page of the phone book, etc.
Sampling TechniquesConvenience
• Sample is selected based on easy access for the researcher.
• EX: You survey your friends or your family, or the people sitting next to you at lunch.
Identify Sampling Techniques (cont.)
• 3. You select the first 5 people who approach you at the mall.
• 4. You assign each person a number and select every 25th person.
• 5. You survey the drama club and the track team to obtain information about student opinions on lunch choices.