Investigation skills assessment

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AQA, ISA Investigation skills assessment definitions.

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Investigation skills assessment (ISA)terms ,[object Object],[object Object],[object Object]

[object Object],Continuous variable Systematic error Categoric variable Reliable Independent variable Evidence Valid Control variable Discrete variable Calibration Zero error Dependent variable Random error Accurate Ordered variable Fair test Precise Data 8 9 7 16 17 18 6 5 14 15 4 13 3 12 11 10 2 1

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Steps of hypothesis testing Select the appropriate test So far we’ve learned a couple variation on z- and t-tests See next slide for how to select State your research hypothesis and your null hypothesis State them in English Then in math Describe the NULL distribution Starting here is where you be a skeptic and assume the null is true! For one-sample tests, you will need to determine μ (For two-tailed tests, you don’t need to worry about μ) Compute the relevant standard error Determine your critical value(s) Keep in mind whether it is a directional or non-directional test Compute the test statistic Compare the test stat to the critical value(s) and make your decision When to use each test All of these tests require that the sampling distribution is normal Either because population is normal or, thanks to central limit theorem, sample size is very large All of these tests require that the measures be quantitative variables, that is interval/ratio (Not all quantitative variables are normal, BUT all normal variables are quantitative. So if someone tells you a variable is normal, you know it is also quantitative.) When to use each test, cont’d 1 Sample z-test Comparing one sample mean to a population mean And you do know σ (population SD) 2 sample z-test Comparing two sample means to each other And you do know σM1-M2 (standard error of difference of means) 1 sample t-test Comparing one sample mean to a population mean You only know s (sample SD) 2 sample t-test Comparing two sample means to each other You only know s1 and s2 (sample SDs) Dependent sample t-test You have two scores coming from each person, such as if you measured them before and after an experimental manipulation. Compute the differences between the two scores, then treat like a 1 sample t What is α? Put on your skeptic’s hat: you believe the null hypothesis is true But you’re willing to be convinced you’re wrong If the test statistic is sufficiently improbable, you will change your mind and decide the null hypothesis is false What is “sufficiently” improbable? When your test statistic is more extreme than your critical values Critical values are selected so that only a small fraction of the entire distribution is more extreme than the critical values This “small fraction” is called α Conventionally, α is usually set to .05, that is 5% Directionality of a test Is a test simply about whether there a difference, regardless of direction? If so, it is a non-directed, or undirected, or two-tailed test Your α must be evenly split between the two tails For the conventional α = .05, that means each tail should have .025 or 2.5% of the total distribution Is the test predicting one mean will be bigger than another? Or is it predicting one mean will be less than another? If so, it a directional, or directed, or one-tailed test Put all your α in a single tail Special note on one-tailed tests Step 3 of our procedure is a little awkward when we have one-tailed tests How do you descr.

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