Linear functions and modeling
- 1. Week 1 LSP 120 Joanna Deszcz Linear Functions and Modeling
- 2. What is a function? Relationship between 2 variables or quantities Has a domain and a range Domain – all logical input values Range – output values that correspond to domain Can be represented by table, graph or equation Satisfies the vertical line test: If any vertical line intersects a graph in more than one point, then the graph does not represent a function.
- 3. What is a linear function? Straight line represented by y=mx + b Constant rate of change (or slope) For a fixed change in one variable, there is a fixed change in the other variable Formulas Slope = Rise Run Rate of Change = Change in y Change in x
- 4. Linear Function QR Definition: relationship that has a fixed or constant rate of change
- 5. Data x y 3 11 5 16 7 21 9 26 11 31 Does this data represent a linear function? We’ll use Excel to figure this out
- 6. Rate of Change Formula (y2- y1) (x2-x1) Example: (16-11) = 5 ( 5-3) 2 x y 3 11 5 16 7 21 9 26 11 31
- 7. In Excel Input (or copy) the data In adjacent cell begin calculation by typing = Use cell references in the formula Cell reference = column letter, row number (A1, B3, C5, etc.) A B C 1 x y Rate of Change 2 3 11 3 5 16 =(B3-B2)/(A3-A2) 4 7 21 5 9 26 6 11 31
- 8. Is the function Linear? If the rate of change is constant (the same) between data points The function is linear
- 9. Derive the Linear Equation General Equation for a linear function y = mx + b x and y are variables represented by data point values m is slope or rate of change b is y-intercept (or initial value) Initial value is the value of y when x = 0 May need to calculate initial value if x = 0 is not a data point
- 10. Calculating Initial Value (b variable) A B C 1 x y Rate of Change 2 3 11 3 5 16 2.5 4 7 21 2.5 5 9 26 2.5 6 11 31 2.5 Choose one set of x and y values We’ll use 3 and 11 Rate of change = m m=2.5 Plug values into y=mx+b and solve for b 11=2.5(3) + b 11=7.5 + b 3.5=bSo the linear equation for this data is: y= 2.5x + 3.5
- 11. Practice – Which functions are linear x y 5 -4 10 -1 15 2 20 5 x y 1 1 2 3 5 9 7 13 x y 2 1 7 5 9 11 12 17 x y 2 20 4 13 6 6 8 -1
- 12. Graph the Line Select all the data points Insert an xy scatter plot Data points should line up if the equation is linear y = 2.5x + 3.5 R² = 1 0 5 10 15 20 25 30 35 0 5 10 15Y-values X - values Linear graph
- 13. Be Careful!!! t P 1980 67.38 1981 69.13 1982 70.93 1983 72.77 1984 74.67 1985 76.61 1986 78.60 66 68 70 72 74 76 78 80 1975 1980 1985 1990PValue t value Not all graphs that look like lines represent linear functions! Calculate the rate of change to be sure it’s constant. t=year; P=population of Mexico
- 14. Try this data t P 1980 67.38 1990 87.10 2000 112.58 2010 145.53 2020 188.12 2030 243.16 2040 314.32 Does the line still appear straight?
- 15. Exponential Models Previous examples show exponential data It can appear to be linear depending on how many data points are graphed Only way to determine if a data set is linear is to calculate rate of change Will be discussed in more detail later
- 16. Linear Modeling andTrendlines Mathematical Modeling
- 17. Uses of Mathematical Modeling Need to plan, predict, explore relationships Examples Plan for next class Businesses, schools, organizations plan for future Science – predict quantities based on known values Discover relationships between variables
- 18. What is a mathematical model? Equation Graph or Algorithm that fits some real data reasonably well that can be used to make predictions
- 19. Predictions 2 types of predictions Extrapolations predictions outside the range of existing data Interpolations predictions made in between existing data points Usually can predict x given y and vise versa
- 20. Extrapolations Be Careful - The further you go from the actual data, the less confident you become about your predictions. A prediction very far out from the data may end up being correct, but even so we have to hold back our confidence because we don't know if the model will apply at points far into the future.
- 21. Let’s Try Some Cell phones.xls MileRecords.xls
- 22. Is the trendline a good fit? 5 Prediction Guidelines Guideline 1 Do you have at least 7 data points? ▪ Should use at least 7 for all class examples ▪ more is okay unless point(s) fails another guideline ▪ 5 or 6 is a judgment call ▪ How reliable is the source? ▪ How old is the data? ▪ Practical knowledge on the topic
- 23. Guideline 2 Does the R-squared value indicate a relationship? Standard measure of how well a line fits R2 Relationship =1 perfect match between line and data points =0 no relationship between x and y values Between .7 and 1.0 strong relationship; data can be used to make prediction Between .4 and .7 moderate relationship; most likely okay to make prediction < .4 weak relationship; cannot use data to make prediction
- 24. Guideline 3 Verify that your trendline fits the shape of your graph. Example: trendline continues upward, but the data makes a downward turn during the last few years verify that the “higher” prediction makes sense See Practical Knowledge
- 25. Guideline 4 Look for Outliers Often bad data points Entered incorrectly Should be corrected Sometimes data is correct Anomaly occurred Can be removed from data if justified
- 26. Guideline 5 Practical Knowledge How many years out can we predict? Based on what you know about the topic, does it make sense to go ahead with the prediction? Use your subject knowledge, not your mathematical knowledge to address this guideline