Bivariate Data.

Slides:



Advertisements
Similar presentations
Bivariate Data Report Structure.
Advertisements

Section 6.1: Scatterplots and Correlation (Day 1).
LSRL Least Squares Regression Line
Two Variable Analysis Joshua, Alvin, Nicholas, Abigail & Kendall.
2.4 Trends, Interpolation and Extrapolation. Line of Best Fit a line that approximates a trend for the data in a scatter plot shows pattern and direction.
1.4 Data in 2 Variables Definitions. 5.3 Data in 2 Variables: Visualizing Trends When data is collected over long period of time, it may show trends Trends.
Objective: I can write linear equations that model real world data.
Prior Knowledge Linear and non linear relationships x and y coordinates Linear graphs are straight line graphs Non-linear graphs do not have a straight.
New Seats – Block 1. New Seats – Block 2 Warm-up with Scatterplot Notes 1) 2) 3) 4) 5)
Section 2.5 – Linear Models. Essential Understanding Sometimes it is possible to model data from a real-world situation with a linear equation. You can.
Notes Bivariate Data Chapters Bivariate Data Explores relationships between two quantitative variables.
Then/Now You wrote linear equations given a point and the slope. (Lesson 4–3) Investigate relationships between quantities by using points on scatter plots.
STATISTICS 12.0 Correlation and Linear Regression “Correlation and Linear Regression -”Causal Forecasting Method.
3.2: Linear Correlation Measure the strength of a linear relationship between two variables. As x increases, no definite shift in y: no correlation. As.
April 1 st, Bellringer-April 1 st, 2015 Video Link Worksheet Link
5.4 Line of Best Fit Given the following scatter plots, draw in your line of best fit and classify the type of relationship: Strong Positive Linear Strong.
Financial Statistics Unit 2: Modeling a Business Chapter 2.2: Linear Regression.
 For each given scatter diagram, determine whether there is a relationship between the variables. STAND UP!!!
.  Relationship between two sets of data  The word Correlation is made of Co- (meaning "together"), and Relation  Correlation is Positive when the.
Section 1.6 Fitting Linear Functions to Data. Consider the set of points {(3,1), (4,3), (6,6), (8,12)} Plot these points on a graph –This is called a.
Scatter Plots. Scatter plots are used when data from an experiment or test have a wide range of values. You do not connect the points in a scatter plot,
Scatter plots. Like a line graph Has x and y axis Plot individual points.
Unit 5: Regression & Correlation Week 1. Data Relationships Finding a relationship between variables is what we’re looking for when extracting data from.
Scatter Plots & Lines of Best Fit To graph and interpret pts on a scatter plot To draw & write equations of best fit lines.
1.How much longer does it take for object B to travel 40 yards than it takes for object A? 2.How much further has object A traveled in 10 seconds than.
Correlation Definition: Correlation - a mutual relationship or connection between two or more things. (google.com) When two set of data appear to be connected.
LINEAR GRAPHS AND FUNCTIONS UNIT ONE GENERAL MATHS.
Correlation & Linear Regression Using a TI-Nspire.
CCSS.Math.Content.8.SP.A.1 Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities.
Chapter 2 Bivariate Data Scatterplots.   A scatterplot, which gives a visual display of the relationship between two variables.   In analysing the.
1 Press Ctrl-A ©G Dear 2009 – Not to be sold/Free to use CorrelationCoefficient Stage 6 - Year 11 General Mathematics HSC.
Correlation of a Scatter Plot. What is correlation… O It describes the direction and strength of a straight-line relationship between two quantitative.
Pearson’s Correlation Coefficient
GCSE: Scatter Diagrams
Lesson 4.5 Topic/ Objective: To use residuals to determine how well lines of fit model data. To use linear regression to find lines of best fit. To distinguish.
MATH 2311 Section 5.1 & 5.2.
Objectives Fit scatter plot data using linear models.
Regression and Correlation
Scatterplots and Correlation
Georgetown Middle School Math
Scatter Plots.
LSRL Least Squares Regression Line
Bivariate Data.
Scatterplots A way of displaying numeric data
Interpret Scatterplots & Use them to Make Predictions
Chapter 3: Linear models
Describe the association’s Form, Direction, and Strength
Suppose the maximum number of hours of study among students in your sample is 6. If you used the equation to predict the test score of a student who studied.
5-7 Scatter Plots and Trend Lines
2. Find the equation of line of regression
AGENDA: Quiz # minutes Begin notes Section 3.1.
Lesson 9-1 Scatter Plots Obj: I can create and interpret scatter plots HWK: p all Vocab: 1) scatter plot 2) correlation 3) positive correlation.
Algebra 1 Section 6.6.
The Weather Turbulence
Correlation Coefficient
Scatterplots and Correlation
Lesson 9-1 Scatter Plots Obj: I can create and interpret scatter plots HWK: p all Vocab: 1) scatter plot 2) correlation 3) positive correlation.
7.1 Draw Scatter Plots & Best-Fitting Lines
Objective: Interpret Scatterplots & Use them to Make Predictions.
Scatter Plots Unit 11 B.
Does age have a strong positive correlation with height? Explain.
MATH 2311 Section 5.1.
Scatterplots line of best fit trend line interpolation extrapolation
Does age have a strong positive correlation with height? Explain.
Bivariate Data credits.
Correlation & Trend Lines
Relations P.O.D. #37 March
Plan for Today: Chapter 14: Describing Relationships: Scatterplots and Correlation.
Scatter Plots Learning Goals
Review of Chapter 3 Examining Relationships
Presentation transcript:

Bivariate Data

Bivariate data Sets of data represented by two variables. Eg. no. of electrical appliances vs Cost of electricity bill. Independent variable – no. of appliances Dependent variable – electricity bill

For each of the following, state the independent and dependent variables. 1. House prices and the no. of bedrooms in those houses 2. Gelato sales and the temperature 3. No. of hours spent studying for a Mathematics test and the score on that test.

Scatter plots - Used to display bivariate data Dependent variable Independent variable

Example

correlation Form – linear or non-linear Direction – positive or negative Strength – strong, moderate or weak Linear Non- linear

Positive Negative

Draw a scatterplot for the following data. Max temp 20 22 24 25 26 28 30 31 Gelato sales 165 180 200 223 250 271 285 300 Describe the correlation between the two variables. Linear or non-linear? Positive or negative? Strength? Make conclusions about the relationship between temperature and gelato sales.

Confidence Predicted values are only indications of what might happen Interpolation – prediction within range of points. More confidence. Extrapolation – prediction outside range of points. Less confidence.