2. Make observations to state the problem *a statement that defines the topic of the experiments and identifies the relationship between the two variables to be tested. *It is a cause and effect relationship where the change or manipulation of a variable will cause the response by another variable. *The relationship must be TESTABLE and the response must be MEASURABLE. This all means that—”The effect of the (independent or manipulated variable) upon the cause of the (dependent or responding variable).”

3. Form a Hypothesis *Make a prediction of what you think will happen next! *Written as an “If….then…” statement *Formats: If the (independent variable) is (changed), then the (dependent variable) will (change) because of (your reasoning). (Changing) the (independent variable) will cause the (dependent variable) to (change) because of (your reasoning).

4. Form a Hypothesis *Make a prediction of what you think will happen next! *Written as an “If….then…” statement *Used to predict a trend NOT just a single outcome! *Your prediction may be true or not true….that is why an experiment must be performed!

5. Determining and Defining Variables *A variable is a factor or condition which can change change during an experiment. *Change only one variable to determine its effect upon another variable. *Must identify all other variables and keep them normal or constant.

6. Determining and Defining Variables Three Types of Variables INDEPENDENT VARIABLE the factor being purposely changed or manipulated. the changes that you make to this variable will cause the changes that you measure

7. Determining and Defining Variables Three Types of Variables INDEPENDENT VARIABLE the factor being purposely changed or manipulated. must determine the level: the amount or concentration determine the trials: the number of times the test is repeated

8. Determining and Defining Variables Three Types of Variables DEPENDENT VARIABLE the factor which responds to the change in the IV. this is the response you predicted! its response is measured as data Must designate how you will measure this variable.

9. Determining and Defining Variables Three Types of Variables CONSTANT (CONTROLLED) VARIABLE not manipulated during the experiment these are often potential IV for future experiments

10. MATERIALS AND PROCEDURE *Simply a recipe for your experiment list of materials step by step instructions Must be very SPECIFIC! state how the response of the DV should be measured

11. QUALITATIVE DATA *data collected by using your senses (are not measured) *simply descriptions organized into tables, diagrams or by drawing pictures

12. QUANTATIVE DATA MEASUREMENTS *the ratio of the magnitude (how much) of a quantity to a standard value, a unit. *all measurements require a magnitude and unit!

13. QUANTATIVE DATA MEASUREMENTS *Measurements are never perfect! So, the uncertainty of a measurement is determined by the scale of the measuring device. Accuracy is the closeness of a measurement to the true value of what is being measured. *depends upon the quality and calibration of the instrument Precision indicates how close individual measurements agree. *depends upon the calibration and the adjustment of the instrument

14. QUANTATIVE DATA MEASUREMENTS Estimate Guidelines for Common Measuring Instruments Measuring Instrument Smallest Increment Record To Nearest Metric ruler1 mm0.1 mm Graduated cylinder1 mL0.1 mL Celsius thermometer 2 ⁰C 1 ⁰C Triple beam balance0.1 g0.01 g

15. Organizing Data Data Tables *has columns and rows *IV recorded in left column *DV recorded in right column *records repeated trials *IV values recorded smallest to largest TrialsIndependent Variable Dependent Variable 1 2 3

16. Organizing Data Data Tables  Must have a title *includes purpose of experiment and both the IV and DV  Must include units for all measurements  If more than one table per lab report then number each table: *number to the left of the title  Tell who collected data by placing name below the table on the left side TrialsIndependent Variable Dependent Variable 1 2 3

17. Organizing Data Graphs  Always create equally spaced increments!  Title must be centered above graph *number each graph *includes experiment purpose and both IV and DV  X and Y axis must have a title and units  Include a legend that has more than one set of data  Write the source below graph on left side

18. Organizing Data Graphs  Pie Graphs *used to show percentages *circle represents the whole and slices represents percentages

19. Organizing Data Graphs  Histographs or Bar Graphs *use when there are various kinds of things *use when the IV has no standard numerical scale *bar represents the count or amount of things

20. Organizing Data Graphs  Line Graphs *used for continuous data *IV goes on the x-axis DV goes on the y-axis

21. Organizing Data Graphs  Line Graphs--SCALING the GRAPH *find the highest and lowest value on axis *if numbering begins at zero, use as lowest value *find the difference between the highest and lowest value *divide the difference by the number of boxes along axis *each box must have the same value increment

22. Organizing Data Graphs  Line Graphs—Plotting *find the value for each point and place a mark where the two values would intersect Drawing the “line of best fit” *examine the points and the graph, draw a line through as many points as possible with even number of unconnected points on each side of the line *points far away from the connected points are to be considered human error

23. Organizing Data Graphs  Line Graphs—Human Errors *Circle points which represent human error (mistakes) *explain by way of notation what caused the human mistake

24. Analyzing Data STATISTICAL ANALYSIS  Measurement of Central Tendency *Mean is the average. Used to analyze random error. *Median is the middle value. *Mode is the value that occurs most frequently or often.

25. Analyzing Data STATISTICAL ANALYSIS  Measurement of Variation *Range is the difference between the high value and the low value. Range = (largest value) – (smallest value)

26. Analyzing Data STATISTICAL ANALYSIS  Measurement of Variation *Standard Deviation is a measure of how closely the individual data points cluster around the mean or the square root of the average squared deviation from the mean. σ

27. Analyzing Data STATISTICAL ANALYSIS  Measurement of Variation *Standard Deviation σ σ lower case sigma is the standard deviation ∑ capital sigma is the sum of the x bar is the mean

28. Analyzing Data STATISTICAL ANALYSIS *Standard Deviation σ To calculate: 1. Find the mean ( ). 2. Subtract the mean from each individual measurement. (x - ) 3. Square each difference from step 2. (x - ) 2 4. Add all of the individual squared differences to obtain a total. 5. Divide the total of the squared differences by the number of measurements minus one. 6. Take the square root of the answer from step 5.

29. Analyzing Data STATISTICAL ANALYSIS *Standard Deviation σ If your data values are widely dispersed ("all over the place"), then the standard deviation of the data values will be relatively large. This might indicate poor experimental technique (which is bad) or malfunctioning equipment.

30. Analyzing Data STATISTICAL ANALYSIS *Standard Deviation σ If your data values are tightly grouped about a mean value the standard deviation will be a relatively small number.

31. Analyzing Data STATISTICAL ANALYSIS  Amount of Error--Percent Error *is a measure of how close an experimental value is to the expected value. *calculated only when the expected value is known. % error = (observed – expected) x 100 expected

32. Analyzing Data STATISTICAL ANALYSIS  Amount of Error--Percent Difference *is a measure of the comparison of two or more experimental measurements. *used to measure the precision of the instrument % difference = (largest value – smallest value) mean

33. Conclusion *is where you put everything together! *a summary of your entire experiment. *whoever reads this must know what was done and what happened.