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# What is the Nature of Science?

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1. What is the Nature of Science? • The Nature of Science is a logical, sequential way of investigating our world. • We wonder, what would happen if I …? • Then we devise a scientific investigation to explore this idea. • Scientific investigations have required parts, and a required order.

2. Variables • Variables are the components that change in a scientific investigation. The components must be measurable. There are 2 types of variables: • The independent variable is the component that the investigator changes. It is graphed on the x axis. There is only 1 independent variable. • The dependent variable is the component that changes due to the independent variable. It is graphed on the y axis. There is only 1 dependent variable.

3. Constants • In a valid scientific investigation, we change 1 variable (independent) and measure the effect on 1 other variable (dependent). • All other components must remain the same! • Components that don’t change in a scientific investigation are called constants.

4. Constants - 2 • For example, we might investigate how amount of sunshine affects plant growth. • We would change the daily amount of sunshine (independent variable) and measure the amount of plant growth (dependent variable). • What would some constants be? • Amount of water, type of plant, type of soil, temperature of the environment, etc – all must stay the same!

5. Control • But we would also need to know if sunshine affects plant growth at all, so we need a control – in which we measure the dependent variable when the independent variable = 0. • For this experiment, the control would be the amount of growth for a plant with no daily sunshine.

6. Hypothesis • A hypothesis is a statement that links the independent to the dependent variable. • It is often written in this form: If the independent variable does this, then the dependent variable will do this.

7. Hypothesis - 2 • For our earlier experiment (amount of sunshine and plant growth), an acceptable hypothesis would be: • If the amount of sunshine increases, the amount of plant growth will increase.

8. Hypothesis - 3 • What would be another valid hypothesis? • If the amount of sunshine increases, the amount of plant growth will decrease. • Or • If the amount of sunshine increases, the amount of plant growth will remain unchanged.

9. Hypothesis - 4 • 2 purposes for a hypothesis: • To get you thinking about the experiment • To get you invested in the outcome • A hypothesis is NOT judged on correctness – it is unacceptable to go back and change your hypothesis to reflect what actually happened!

10. Data • Data is collected through observation – using 1 or more of the 5 senses. • Examples of observation: • seeing the volume in a graduated cylinder • smelling the sulfur odor from a chemical • hearing the tick of the metronome, etc.

11. Analysis • Anything done to the data is analysis. • Analysis includes: • graphing • identifying trends • making calculations • estimating amount and types of error, etc.

12. Graphing • Types of graphs and common uses: • A circle graph is for percentages. • A bar graph is for data that occurs in categories (grades, months, m/f, etc) – called “discrete” data. • A line graph is for continuous data.

13. Graphing - 2 • A correct line graph has: • a relevant title, • each axis is labeled including units, • each axis has a consistent scale, • points are plotted, • a line or curve of best fit is drawn (going thru as many points as possible, and with as many points above the line as below)

14. Graphing - 3 • If the data points appear to be linear, graph it as a line of best fit. • If the data points appear to be curved, graph it as a smooth curve of best fit. • Since we are looking for trends or patterns, very rarely do we “connect the dots” when graphing in science!

15. Identifying trends • Trends are either: • Direct relationship – when one value increases the other value also increases  or  or a line with a positive slope • Inverse relationship – when one value increases the other value decreases  or a line with a negative slope • No relationship – either too varied to be determined, or remains constant (a line with 0 slope)

16. Making calculations • Suppose your task is to find the density of an object. Your lab equipment can measure mass and volume. You can calculate density as mass/volume. Mass and volume are data, the calculation for density is analysis (since you didn’t directly observe it). • Often we graph linear data and calculate the slope of the line. • Slope = (y2 – y1)/(x2 – x1)

17. Making calculations - 2 What is the slope of this line?

18. Making calculations - 3 • The equation for a line is y = mx + b • m is the slope,and b is the y-intercept. • What would be the equation for the previous graph? • y = (.00625 kgm-2/mm)x + .13kgm-2 • What is y measuring? • What is x measuring? • Cucumber yield = (.00625 kgm-2/mm)precipitation + .13kgm-2

19. Estimating Error • Measurement errors can be categorized as 2 types: • Random – caused by the person making the measurement. Random errors can be reduced by repeating the measurement and taking the average. • Systematic – caused by the system or equipment used to make the measurement.

20. Estimating Error - 2 • Ways we will calculate: • % error is used when comparing an experimental value to a known, standard theoretical value (such as atomic mass, acceleration due to gravity): • % error = (|theo – exp| / theo) x 100 • % difference is used when comparing 2 experimental values: • % diff ={|val 1 – val 2| / [1/2 (val 1 + val 2)]} x 100 • Handout: Calculating uncertainties for IB

21. Estimating Error - 3 • You found carbon’s mass to be 11.5 amu. Your textbook lists it as 12.0 amu. What is the % error? • 4.2 % • You measured an object’s mass as 25.7 g and your lab partner measured it as 26.9 g. What is the % difference? • 4.6 %

22. Human Error Activity • 6 stations each with a designated task • Perform each task, record your results • For each station, calculate % difference between your value and Mrs. G’s value • Calculate an overall average of your differences • Don’t turn it in yet! Be ready to share!