ISA Glossary of Terms Use this PowerPoint to help you explain the AQA Glossary of Terms in preparation for an ISA for the 2013 course. 20/09/2018

Variables Variables can be described in a number of ways: 1) Categoric – categoric variables have values that are labels, e.g. eye colour 2) Continuous – continuous variables have a numerical value, e.g. the number of pets you have or your height 3) Control – a control variable is one that could affect the outcome of the experiment but you keep it the same 4) Independent – the independent variable is the one that you will change during your experiment 5) Dependent – the dependent variable is the one that will be measured after changing the independent variable 20/09/2018

Validity, Fair Tests and Evidence For an experiment to be “valid” it must be a fair test, e.g: I’m investigating how quickly acid reacts with marble chips. I want to know if the concentration of the acid affects the reaction rate. Here are my results: Concentration of acid Temperature reaction happened at/OC Time taken for reaction to finish/s Low 20 30 High 50 100 Clearly, the stronger the acid, the quicker the reaction. Was this experiment valid? Was it a fair test? Can this data be classed as “evidence”? 20/09/2018

Data Here are my results. I think I’ll draw a graph of them as this is “quantitative data”, e.g. the number of people who have different hair colour. I’ve also got some results but mine are descriptive or written in words – this is “qualitative data”, e.g. my hair colour. 20/09/2018

I want to use this big tube as a thermometer. How could I do it? Calibration I want to use this big tube as a thermometer. How could I do it? Step 1: Mark where a liquid would be at a known value, e.g. 100OC Step 2: Mark where the liquid would be at a second known value, e.g. 0OC Step 3: Mark on a scale by dividing the length by 100 sections – each section represents 1OC. Now it is calibrated! 20/09/2018

Calibration Here’s another example of using a known quantity to calibrate something: 20/09/2018

Time taken to complete 1 swing/s Resolution You have a choice of two thermometers: What is the resolution of each thermometer? What is the resolution of the stopwatch used in the experiment below? Length of pendulum/cm Time taken to complete 1 swing/s 10 0.63 20 0.90 30 1.10 40 1.27 50 1.42 20/09/2018

True Value and Accuracy The “true value” is the value that would be obtained with ideal measurements. A measurement is judged to be “accurate” if it close to that value. For example, what does this thermometer read? I reckon it’s 22OC I reckon it’s 24OC My measurement was the most accurate as it was closest to the true value! I reckon it’s 26OC 20/09/2018

Uncertainty Consider the same thermometer readings again: Is it 22OC, 24OC or 26OC? “Uncertainty” means “the interval within which the true value would lie” with a given level of probability, e.g. “the temperature is 24OC ± 2OC, to within a probability of 95%”. What uncertainty was there within your results? 20/09/2018

Unlucky. I’m actually 175cm tall. Measurement Error A “measurement error” is defined as “the difference between a measured value and the true value”, e.g: Here’s my friend. I’ve just measured him with a metre ruler and I think he’s 170cm tall. Unlucky. I’m actually 175cm tall. What is the difference between these results and what is the percentage difference between them? 20/09/2018

Time taken for magnesium to react/s Precision “Precise measurements” are measurements that show very little spread around the mean average value. Which of the following two sets of data are the most precise? Conc. of acid Time taken for magnesium to react/s Average time/s Attempt 1 Attempt 2 Attempt 3 Low 50 52 54 High 20 24 22 Notice that precision depends only on random errors – it gives no indication of how close results are to the true value! 20/09/2018

Anomalous Results Here’s a graph that shows us how the temperature of hot water varies when it is left in a cold room. What would you do with these results? Temperature of water/OC x x x x x x x x 20/09/2018 Time/mins

Random errors Random errors can occur with any experiment but some experiments can have more random errors than others. For example, here are two experiments: Hooke’s law, where different forces are hung on a spring and the extension is measured. Choice chambers, where woodlice are “invited” to choose their living conditions. Which one of these experiments would probably have the most random errors and what would do about it? 20/09/2018

What’s wrong with this balance reading? 20/09/2018

Notice that a zero error usually results in a systematic uncertainty. Systematic Error A systematic error is one where the measurement differs from the true value by a consistent amount each time, e.g: Notice that a zero error usually results in a systematic uncertainty. 20/09/2018

Systematic Errors on a Graph x Resistance of wire/Ω According to this graph, a wire that’s zero cm long has some resistance, which can’t be right. What went wrong? Length of wire/cm 20/09/2018

Ranges and Intervals “Range” represents the range from the lowest and highest values for a variable. “Interval” represents the quantity between readings. For example, consider the following experiment: Length of pendulum/cm Time taken to complete 1 swing/s 10 0.63 20 0.90 30 1.10 40 1.27 50 1.42 What is the range and interval of these lengths? 20/09/2018

“Repeatable” and “Reproducible” Here are my results sir. I did the experiment 3 times using the same method and equipment and got the same results each time. Here are my results sir. I followed the same method as my friend and got the same results. This data is judged to be “reliable” as it stayed the same after several different measurements. Q. Which experiment shows “repeatable” data and which one shows “reproducible” data? 20/09/2018

Supporting or rejecting a hypothesis If our results agree with our hypothesis, we say they support it If our results disagree with our hypothesis, we say they reject it When explaining your results, you must use examples to demonstrate how they either support or reject your hypothesis My results support my hypothesis because the longer the length of the pendulum, the longer time it takes to do one swing. The longest pendulum had the longest swing, at 1.42 seconds, compared to the shortest pendulum which had a swing time of 0.62 seconds

Drawing a conclusion Here’s a simple experiment where the rate of cooling is investigated when hot water is covered in different numbers of layers: 20/09/2018

Writing a valid conclusion A bad conclusion: A simple statement saying what your results show. A good conclusion: A detailed statement showing what your results show AND a description of other patterns, e.g. what happens between 4 and 5 layers of insulation? Why did this happen? Is your graph a straight line or a curve? Do your results show proportionality? If the experiment was designed well, the data is valid (i.e. from a fair test) and the conclusion accurately explains what the data shows then we call the conclusion “valid” 20/09/2018

Q. What would be a good conclusion for these results? Drawing a conclusion Temperature of water/OC x x 3 layers x x x x x x x No layers Q. What would be a good conclusion for these results? Time/mins 20/09/2018

Temperature after ___ mins/OC Anomalous Results Where are the two anomalous results and what caused them? No. of layers Initial temp/ OC Temperature after ___ mins/OC Temp change/ 1 2 3 4 5 6 7 8 9 10 70 68 65 62 59 57 55 53 50 47 44 26 66 63 75 60 51 20 69 67 61 58 56 54 52 28 13 71 12 20/09/2018

Evaluating your method Did you get reliable, reproducible, repeatable, valid and precise results? If not, why not? If not, how could you improve your method to make them better? It was difficult to measure accurately because the thing I was measuring kept moving, so I wasn’t sure it lined up right. I would change my method to measure it more accurately, and reduce this systematic error. I wouldn’t change my method because my results showed a clear pattern and I did a suitable number of repeats. I also controlled my variables so my results are valid, and doing it differently wouldn’t change anything.

Calculating mean values To calculate the mean value of a range of results, follow the following steps: Add the numbers up Press the equals button Divide by how many numbers you added For example, calculate the mean average of the following: 8, 10, 12 104, 106, 88 34, 56, 40 20/09/2018

Sketch Graphs A sketch graph is one that “sketches” the relationship between two different variables without plotting any points. For example: Temperature of water/OC Time/mins Sketch a graph to show how the temperature of a hot cup of coffee will change over time: Sketch a graph to show how the rate of CO2 produced during photosynthesis varies with temperature: 20/09/2018

Which graph? Line graphs Bar charts Used for “continuous” variables, e.g. height, weight, length, temperature, time etc Used for “discrete” or “categoric” variables, e.g. number of people, eye colour etc 20/09/2018

Task Choose one term, and produce a colourful poster giving its meaning to be displayed in the class. You have a copy of the PowerPoint to help direct you.