Statistics Vocabulary. 1. STATISTICS Definition The study of collecting, organizing, and interpreting data Example Statistics are used to determine car.

Slides:



Advertisements
Similar presentations
Describing Quantitative Variables
Advertisements

Unit 1.1 Investigating Data 1. Frequency and Histograms CCSS: S.ID.1 Represent data with plots on the real number line (dot plots, histograms, and box.
Statistics It is the science of planning studies and experiments, obtaining sample data, and then organizing, summarizing, analyzing, interpreting data,
Variability Measures of spread of scores range: highest - lowest standard deviation: average difference from mean variance: average squared difference.
Descriptive Statistics
Introduction to Educational Statistics
Very Basic Statistics.
12.3 – Measures of Dispersion
Statistics: Use Graphs to Show Data Box Plots.
Descriptive Statistics  Summarizing, Simplifying  Useful for comprehending data, and thus making meaningful interpretations, particularly in medium to.
Describing Data: Numerical
Describing distributions with numbers
Chapter 1 Descriptive Analysis. Statistics – Making sense out of data. Gives verifiable evidence to support the answer to a question. 4 Major Parts 1.Collecting.
Descriptive Statistics  Summarizing, Simplifying  Useful for comprehending data, and thus making meaningful interpretations, particularly in medium to.
Descriptive Statistics Used to describe the basic features of the data in any quantitative study. Both graphical displays and descriptive summary statistics.
Census A survey to collect data on the entire population.   Data The facts and figures collected, analyzed, and summarized for presentation and.
CHAPTER 1 Basic Statistics Statistics in Engineering
1 Excursions in Modern Mathematics Sixth Edition Peter Tannenbaum.
© Copyright McGraw-Hill CHAPTER 3 Data Description.
Are You Smarter Than a 5 th Grader?. 1,000,000 5th Grade Topic 15th Grade Topic 24th Grade Topic 34th Grade Topic 43rd Grade Topic 53rd Grade Topic 62nd.
Section 1.1 What is Statistics.
STAT 280: Elementary Applied Statistics Describing Data Using Numerical Measures.
© 2006 McGraw-Hill Higher Education. All rights reserved. Numbers Numbers mean different things in different situations. Consider three answers that appear.
By: Amani Albraikan 1. 2  Synonym for variability  Often called “spread” or “scatter”  Indicator of consistency among a data set  Indicates how close.
14.1 Data Sets: Data Sets: Data set: collection of data values.Data set: collection of data values. Frequency: The number of times a data entry occurs.Frequency:
Statistics 2. Variables Discrete Continuous Quantitative (Numerical) (measurements and counts) Qualitative (categorical) (define groups) Ordinal (fall.
An Introduction to Statistics. Two Branches of Statistical Methods Descriptive statistics Techniques for describing data in abbreviated, symbolic fashion.
The Central Tendency is the center of the distribution of a data set. You can think of this value as where the middle of a distribution lies. Measure.
An Overview of Statistics Section 1.1. Ch1 Larson/Farber 2 Statistics is the science of collecting, organizing, analyzing, and interpreting data in order.
A Short Tour of Probability & Statistics Presented by: Nick Bennett, Grass Roots Consulting & GUTS Josh Thorp, Stigmergic Consulting & GUTS Irene Lee,
Unit 4: Describing Data After 8 long weeks, we have finally finished Unit 3: Linear & Exponential Functions. Now on to Unit 4 which will last 3 weeks.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Statistics is The study of how to: collect organize analyze interpret numerical information.
CCGPS Advanced Algebra UNIT QUESTION: How do we use data to draw conclusions about populations? Standard: MCC9-12.S.ID.1-3, 5-9, SP.5 Today’s Question:
The field of statistics deals with the collection,
CCGPS Advanced Algebra Day 1 UNIT QUESTION: How do we use data to draw conclusions about populations? Standard: MCC9-12.S.ID.1-3, 5-9, SP.5 Today’s Question:
Statistics topics from both Math 1 and Math 2, both featured on the GHSGT.
LIS 570 Summarising and presenting data - Univariate analysis.
Statistics with TI-Nspire™ Technology Module E Lesson 1: Elementary concepts.
CCGPS Advanced Algebra Day 1 UNIT QUESTION: How do we use data to draw conclusions about populations? Standard: MCC9-12.S.ID.1-3, 5-9, SP.5 Today’s Question:
Descriptive Statistics(Summary and Variability measures)
Exploratory data analysis, descriptive measures and sampling or, “How to explore numbers in tables and charts”
What is Statistics?. Statistics 4 Working with data 4 Collecting, analyzing, drawing conclusions.
Descriptive Statistics
Exploratory Data Analysis
Notes 13.2 Measures of Center & Spread
EXPLORATORY DATA ANALYSIS and DESCRIPTIVE STATISTICS
Chapter 4 Review December 19, 2011.
CHAPTER 5 Basic Statistics
CHAPTER 3 Data Description 9/17/2018 Kasturiarachi.
Description of Data (Summary and Variability measures)
CHAPTER 1 Exploring Data
Unit 7: Statistics Key Terms
Unit 4 Statistics Review
An Introduction to Statistics
Basic Statistical Terms
Statistics Section 1.1 Apply the vocabulary of statistical measurement
CHAPTER 1 Exploring Data
Describing Quantitative Data with Numbers
CHAPTER 1 Exploring Data
CHAPTER 1 Exploring Data
Unit 4: Describing Data After 10 long weeks, we have finally finished Unit 3: Linear & Exponential Functions. Now on to Unit 4 which will last 5 weeks.
CHAPTER 1 Exploring Data
CHAPTER 1 Exploring Data
CHAPTER 1 Exploring Data
CHAPTER 1 Exploring Data
CHAPTER 1 Exploring Data
CHAPTER 1 Exploring Data
Advanced Algebra Unit 1 Vocabulary
CHAPTER 1 Exploring Data
CHAPTER 1 Exploring Data
Presentation transcript:

Statistics Vocabulary

1. STATISTICS Definition The study of collecting, organizing, and interpreting data Example Statistics are used to determine car insurance rates, home mortgages, etc.

2. INDIVIDUAL Definition person or object in the study Example If a study is about teachers, each teacher interviewed or observed is called an individual.

3. VARIABLE Definition The characteristic of the individual to be observed or measured Example Test scores

4. QUANTITATIVE VARIABLE Definition Variable that quantifies Assigns a numerical value Example A person’s weight

5. QUALITATIVE VARIABLE Definition Variable that categorizes or describes Example Gender

6. POPULATION Definition Every individual of interest Example All living presidents – not just a few of them

7. SAMPLE Definition A subset of the population (some of the individuals of interest) Example Some living presidents

8. NOMIAL DATA Definition Data consisting of only names or qualities No numerical values Example Colors

9. ORDINAL DATA Definition Data that has an order but differences between data values are meaningless Example Student high school rankings (1 st, 9 th, 28 th, etc)

10. INTERVAL DATA Definition Data that has an order, meaningful differences, but may or may not have a starting point which makes ratios meaningless Example Temperature readings

11. RATIO DATA Definition Data with the same characteristics as interval data but with a starting point which makes ratios meaningful Example Measures of hei

12. DESCRIPTIVE STATISTICS Definition The practice of collecting, organizing, and summarizing information from samples or populations Example Graphs, measures of center and spread

13. INFERENTIAL STATISTICS Definition The practice of interpreting sample values gained from descriptive techniques and drawing conclusions about the population Example Polling 100 voters and using the results to predict a winner

14. STANDARD DEVIATION Definition A measure of how spread out numbers are. Its symbol is σ (the greek letter sigma) The formula is easy: it is the square root of the Variance. Formulas The "Population Standard Deviation“ The "Sample Standard Deviation

15. VARIANCE Definition The average of the squared differences from the Mean. To calculate the variance follow these steps: – Work out the Mean – Then for each number: subtract the Mean and square the result (the squared difference). – Then work out the average of those squared differences.

16. DISCRETE DATA Definition Is counted Can only have certain values Example Number of students in a class (Can’t have half a student); numbers on a die

17. CONTINUOUS DATA Definition Is measured Can take any value within a range Example A person's height: could be any value (within the range of human heights), not just certain fixed heights, Time in a race: you could even measure it to fractions of a second, A dog's weight, The length of a leaf,

18. Range (Statistics) Definition The difference between the lowest and highest values. Example In {4, 6, 9, 3, 7} the lowest value is 3, and the highest is 9. – So the range is 9-3 = 6.

19. Quartiles Definitions The values that divide a list of numbers into quarters. Examples First put the list of numbers in order Then cut the list into four equal parts. The Quartiles are at the "cuts" Example: 5, 8, 4, 4, 6, 3, 8 – Put them in order: 3, 4, 4, 5, 6, 8, 8 – Cut the list into quarters: – And the result is: Quartile 1 (Q1) = 4 Quartile 2 (Q2), which is also the Median, = 5 Quartile 3 (Q3) = 8

20. INTERQUARTILE RANGE Definition The "Interquartile Range" is from Q1 to Q3. To calculate it just subtract Quartile 1 from Quartile 3. Example The Interquartile Range is: Q3 - Q1 = = 4

Data Displays Advantages & Disadvantages

Line Plot Advantages Individual data is not lost Easy to create Shows range, minimum, maximum, gaps, clusters, & outliers Disadvantages Can be cumbersome if there are a large number of data values Needs a small range of data

Bar Graph Advantages Easy to create Easy to read Makes comparisons easy Disadvantages Only used for discrete data Individual data is lost

Circle Graph Advantages Easy to read Shows percentages Disadvantages Only used for discrete data Individual data is lost Good for only about 3- 7 categories Total is often missing

Stem-Leaf Plot Advantages Easy to create Stores a lot of data in a smaller space Shows range, minimum, maximum, gaps, clusters, & outliers Disadvantages Can be cumbersome if there are a large number of data values Can be difficult to read Not visually appealing

Box Plot Advantages Identifies outliers Makes comparisons easy Shows 5-point summary (minimum, maximum, 1 st Quartile, Median, & 3 rd Quartile) Disadvantages Individual data is lost Can be confusing to read Not visually appealing