1. EXCEL DECISION MAKING TOOLS AND CHARTS BASIC FORMULAE - REGRESSION - GOAL SEEK - SOLVER

2. EXCEL BASIC FORMULAE. Name Cell (Cell Address) Formula Bar (Contents of Cell) Cells can contain Values or Formulas Commas separate values (1,2,3) is 1 and 2 and 3 Colons indicate ranges (A2:A5) is Cell A2 through A5

3. EXCEL BASIC FORMULAE All Formulas begin with = Basic Formulas (numbers, cells, or both) Add +Subtract -Multiply *Divide / =10+5=10-5=10*5=10/5 =B3+C3=B3-C3=B3*C3=B3/C3 =B3+5=B3-5=B3*5=B3/5 =SUM(B3:B5)=SUM(100,-30)=PRODUCT(D4,E9)

4. EXCEL BASIC FORMULAE The AutoSum Feature in Excel (Σ) The AutoSum button quickly inserts Excel functions that summarize all the values in a column or row using a single statistic Sum of the values in a Column or Row Average of the values in Column or Row Total Count of Numeric Values in a Column or Row Max Value of the Column or Row Min Value of the Column or Row

5. EXCEL BASIC FORMULAE

6. The Relative Formula Reference Feature in Excel ($$) Multiplication of B2=A2*B1 becomes C2=B2*C1, this is called relative formula reference. Can be avoided by using the F4 Key and locking the reference cell. $ locks the reference term. $A1 tells Excel you always want to refer to column A. B$1 tells Excel you always want to refer to row 1. $B$1 tells Excel you always want to refer to cell B1. New Formula in B2=B$1*$A2

7. EXCEL BASIC FORMULAE How to Calculate Exponents in Microsoft Excel We Simply want to calculate a number to power of a number As simple and straight forward it is, the formula for this function in excel is straight forward too =POWER() >> i.e. =POWER(number, power). Ref NumberPowerFormulaResult 23=POWER(2,3)8 C33=POWER(C3,3)8 C3D3=POWER(C3,D3)8 2D3=POWER(2,D3)8 Next- Regressions

8. REGRESSION ANALYSIS And Charts

9. Simple Linear Regression Regression: it’s an Add-in Installation: Home Excel options> Add-in Select Analysis Toolpak To Use, Data> Analysis. In pop-up, Choose Regression

10. REGRESSION We Have Ice Cream Data for a 20 Days, Along with the Highest Temperature of the Respective Day Can we use this Data to infer that the Temperature can affect the sales data? Simple look can interpret that there is a relation, but do we have a mathematical proof to support our assumption?

11. REGRESSION “Day 1” has Highest Temp of 65 F and sales 20(in 100’s) “Day 2” has Highest Temp of 68 F and sales 22(in 100’s) “Day 3” has Highest Temp of 66 F and sales 21(in 100’s) So on... For 20 total data samples How can you present this data? SCATTER GRAPH

12. Scatter Graphs Scatter graphs are similar to line graphs in that they use horizontal and vertical axes to plot data points. They have a very specific purpose Scatter plots show how much one variable is affected by another. The relationship between two variables is called their correlation.

13. Temperature Sales 0 65 20 68 30

14. Regression is the attempt to explain the variation in a dependent variable using the variation in independent variables. Regression is thus an explanation of relation. If the independent variable(s) sufficiently explains the variation in the dependent variable, the model can be used for prediction. Independent variable (x) Dependent variable Scatter Graph using Regressions

15. Independent variable (x) Dependent variable (y) The output of a regression is a function that predicts the dependent variable based upon values of the independent variables. b 0, is the point where the line always touches the y –axis, hence y-intercept Simple regression fits a straight line to the data. y’ = b 0 + b 1 X ± є b 0 =y intercept b 1 = slope = ∆y/ ∆x є Simple Linear Regression 1/2

16. Simple Linear Regression Independent variable (x) Dependent variable The function will make a prediction for each observed data point. The observation is denoted by y and the prediction is denoted by y^. Zero Prediction: y Observation: y ^

17. Simple Linear Regression For each observation, the variation can be described as: y = y^ + ε Actual = Prediction + Error Zero Prediction error: ε Prediction: y ^ Observation: y

18. Explaining the Coefficients in an Equation Y = b 1 + b 0 X ; for a single variable simple regression This equation explains how and why one “dependent” variable is determined by an “independent” or “explanatory” variable. On the left side is Y, our dependent variable, Sales. On the right side are b 1 (our constant or intercept) and b 0 (our coefficient or slope) multiplied by X (our independent or explanatory variable), temperature. Y(Sales) = -8.4311 + 0.4311 Temp. But what if we think that the world is much more complicated and that a variety of factors might explain sales?

19. Statistic Terminologies and Indicators T-Statistic Reveals if the coefficients are statistically significant. If your regression is 30 or more observations, a t-statistic greater than 2 (or less than -2) indicates the coefficient is significant with >95% confidence. A t-statistic greater than 1.68 (or less than -1.68) indicates the coefficient is significant with >90% confidence. The confidence thresholds for t-statistics are higher for small sample sizes.

20. Statistic Terminologies and Indicators P-values: These probabilities also reveal if the coefficients are statistically significant. Should be around 0.05 (or less!); the lower the value, the higher the confidence that the estimated slope coefficient is true. The P-value of 0.05 for an coefficient implies 1 - 0.05 = 95%

21. Statistic Terminologies and Indicators Multiple R: Also Known as Correlations It should be around +- 0.5 or more Used when only 2 Values are being compared.

22. GOAL SEEK

23. Goal Seek Single variable Set up properly, select the whole table Data > What-If Analysis > Goal Seek Set Cell: Formula cell To Value: Target/Goal By Changing: Variable required to be changed( first field usually)

24. Loan Amount$100,000 Interest Rate3.75% Repayment120 Months EMI1,001

25. Goal Seek But our budget is just $600 monthly payment How much can we borrow? Let’s use the Goal Seek tool to determine the amount. Goal Seek adjusts the value of the input(s) such that the desired output is achieved

26. Goal Seek Loan Amount $100,000 Interest Rate 3.75% Repayment 120 Months EMI $ 1,001 EMI Cell Desired Value Loan Amount Cell Loan Amount $59963 Interest Rate 3.75% Repayment 120 Months EMI $ 600

27. SOLVER

28. Solver Do you ever think about questions like this? What is the maximum profit we can make? What is the best way to schedule employees in shifts? What the best combination of tasks we can finish in a given time? Here Comes the MS Excel Solver It’s a basic tool which just solves problems for us It’s like Goal Seek but more Advanced

29. Solver Solver: it’s an Add-in Installation: Home Excel options> Add-in Select Analysis Toolpak> Select Data Analysis & Solver, both. To Use, Data> Solver

30. Solver It has 3 Cells Set Target Cell: Should be formula cell you want to change By Changing Cell: Multiple cells can be selected Subject to constraints: Can select multiple constraints

31. WEEKEND TIME Thank You