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Data Collecting, Organizing & Analyzing. VARIABLES & DATA TABLES.

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Presentation on theme: "Data Collecting, Organizing & Analyzing. VARIABLES & DATA TABLES."— Presentation transcript:

1 Data Collecting, Organizing & Analyzing

2 VARIABLES & DATA TABLES

3 w In an experiment there are 2 types of variables INDEPENDENT VARIABLES & DEPENDANT VARIABLES

4 w a VARIABLE is any factor, or thing that can change during your experiment

5 w a CONTROLED experiment only has 1 variable changing, or being tested w Sometimes a control trial or group is used to compare experimental data to

6 INDEPENDENT VARIABLE w This is the variable we can control in an experiment. w Independent variables are set up ahead of time, before you start following your procedures

7 INDEPENDENT VARIABLE w In a T table, or data table, this variable is on the left side. w On a graph, this variable goes on the X axis

8 INDEPENDENT VARIABLE w Examples of common Independent variables: Time-measure every 30 seconds, every day, etc. Distance-measure every 0.5 meters, every 10.0 cm Amount-add 2.0 grams each trial

9 INDEPENDENT VARIABLE w Your book calls the independent variable the MANIPULATED variable, because we manipulate or set it to our specifications

10 DEPENDENT VARIABLE w This is the variable we have to observe in an experiment. w Dependent variables are measured during the experiment, after you start following your procedures

11 DEPENDENT VARIABLE w In a T table, or data table, this variable is on the right side. w On a graph, this variable goes on the Y axis

12 DEPENDENT VARIABLE w Examples of common Dependent variables: Temperature-record the temperature Mass-find the mass of each object or substance Amount-count the resulting number of items

13 DEPENDENT VARIABLE w Your book calls the dependent variable the RESPONDING variable, because it responds to the procedure you are following. We cant chose what the data will be.

14 GRAPHING NOTES

15 7 RULES OF GRAPHING w Follow these simple rules for GREAT GRAPHS

16 RULE # 1. w 1. Always draw neat lines with a straight edge or ruler

17 RULE # 2. w Make your graph 1 full page in size. w Small graphs are too difficult to read patterns or results of your experiment.

18 RULE # 3. w Label the x-axis (goes across the bottom of your graph) w Label the y-axis ( the line that goes up & down on the left side of your graph)

19 RULE # 4. w Label three places on your graph. w 1. TITLE the graph descriptively w WHAT DOES YOUR GRAPH SHOW US?

20 RULE # 4. w 2. label the x-axis with the independent variable this is the variable you pre-set before you began collecting data, on the left side of a T table common independent variables can be time, or distances Data points should be evenly spaced

21 RULE # 4. w 3. label the y-axis with the dependent variable this is the variable you measure when you begin collecting data, on the right side of a T table common dependent variables can be mass, or temperature Data points should be evenly spaced

22 RULE # 5. w Number the x and y axis with a regular numerical sequence or pattern starting with 0 to space out your data so it fills the entire graph examples: 0, 5, 10, 15... 0, 2, 4, 6,.., 0, 0.5, 1.0, 1.5, 2.0

23 RULE # 6. w Number the x and y axis on the lines of the graph, not the spaces between the lines

24 RULE # 7. w If your graph shows more than one trial of data, or has more than 1 line, USE A KEY w A key can be different colored lines, lines with different textures or patterns.

25 Choose the best graph for the data w Pie chart- shows percentages and parts of a whole w Bar graph- best for comparing data w Line graph- best for looking at change over time w Stem & Leaf plot- comparing data that can also show mean, mode, and median

26 Statistical Analysis w Mean- (average)- add up all the data & divide that total by the number of data points ex. : 1,2,3,2,4,2 = 14 14/6= 7/3 or 2.3 w Mode- number seen most often ex:1,2,3,2,4,2 mode is 2 w Median- middle value when data is placed in numerical order Ex.: 1,2,2,2,3,4,5 odd ex:1,2,2,2,3,4 even 2+2=4/2=2 median is 2 w Range- difference between the greatest # and the smallest # in the data set ex.1,2,2,2,3,4 4-1= 3 data vary over 3 values

27 How to change numbers into % for pie charts. w You can refer to your book on page 770. w Determine the total number for your data: add up all the values to get one number. 1,2,2,2,3,4 = 14 w Divide each proportion by the total number. 1/14, 2/14. 3/14, 4/14 w Multiply that decimal by 360. This will give the number of degrees that your pie piece should contain. Ex. 2/14= 0.143 0.143 x 360= 51.4 degrees w Use a protractor to measure the angle of each slice. w To find the percentage take the number of degrees in the slice divide it by 360 and multiply the new number by 100%. 51.4 / 360= 0.143 x 100% = 14.3 %

28 The End Good Luck and Happy Data Collecting!


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