A-level Biology - Practical Skills
A prediction or hypothesis is a clear, testable statement that outlines what you expect to happen in an experiment based on prior knowledge or theory. It often includes both the independent and dependent variables and provides a basis for designing the investigation.
What is a prediction/hypothesis?
Key Terms
What is a prediction/hypothesis?
Specific testable statement about what will happen in experiment
Define precise results
Results that don’t vary much from mean
Define Valid
Free of error
(Valid results answer original question)
How do you obtain valid results?
By controlling all variables to make sure you’re testing thing you want
Define accurate results
Results that really come close to the true value
What can decrease accuracy of results?
Human interpretation of measurement (e.g. determining colour change)
Related Flashcard Decks
| Term | Definition |
|---|---|
What is a prediction/hypothesis? | Specific testable statement about what will happen in experiment |
Define precise results | Results that don’t vary much from mean |
Define Valid | Free of error (Valid results answer original question) |
How do you obtain valid results? | By controlling all variables to make sure you’re testing thing you want |
Define accurate results | Results that really come close to the true value |
What can decrease accuracy of results? | Human interpretation of measurement (e.g. determining colour change) |
How can precision be reduced? | Reduced by random errors |
Define Reproducible | If someone different does experiment, using slightly different method or piece of equipment, results will be the same |
Define Repeatable | If same person repeats experiment using same methods and equipment = get same results |
Define Calibration | Marking a scale on a measuring instrument |
Define Resolution | Smallest change a measuring instrument can detect |
Define a zero error | Systematic error caused by using equipment that isn’t zeroed properly |
Define a random error | Unpredictable way in which all measurements wary (e.g. human errors in measuring) |
How can you reduce the effect of random errors | By repeat readings & finding the mean |
Define a systematic error | Measurement wrong by same amount every time |
Define a measurement error | Difference between measured value and true value |
Define uncertainty | Amount of error your measurements might have |
How can you calculate a percentage error of your measurements? | To calculate percentage error of your measurements, use the following formula: Percentage error=(Uncertainty)/Measured value ×100 |
Name 2 ways you can reduce uncertainty | Using most sensitive equipment available Measure a greater amount of something |
Define categoric variables | Values that are labels e.g. names of plants |
Define nominal variables | Type of categoric variable where there is no ordering of categories e.g. red flowers, pink flowers, blue flowers |
When is it suitable to use a scatter graph? | When you’re looking at relationship between 2 discrete/independent variables |
Name 2 reasons why have a control group with a placebo makes your results more reliable | Removes researcher biasis Control group can’t show psychologial effects |
Data is often given as percentages of people dying from each cause. Explain the advantage of giving these data as percentages. (2) | Easier to compare if sample size effectively the same Different no. of people in each group |
If experimental group are given the treatment via injections, suggest how the control group should be treated (2) | Given only saline Otherwise treated exactly the same way |
What does standard deviation tell you? | Spread from the mean |
Comment on the effectiveness of taxol when used separately and as a combined treatment (related to SD) | SD overlap for OGF with taxol and taxol on its own so not conclusive/could be chance/both treatments effective |
Why should you repeat experiments? | To increase the reliability of your results Anomalies can be identified |
What does an overlap in standard deviation mean? | Unlikely that any difference (in results) is significant |
An investigation was carried out into the effect of carbon dioxide concentration and light intensity on the rate of photosynthesis in a species of plant. The temperature was kept constant during the investigation. Explain why. (2) | Temperature affects the rate of photosynthesis ∴ any change in photosynthesis rate is the result of CO2/light intensity |
Explain how the results from tube D help to confirm that the explanations for the other tubes are valid. (1) | Shows that indicator alone doesn't change colour in light |
Explain the advantages of collecting a large number of results (2) | Easier to spot anomalies/increases reliability of results Allows use of statistical test |
Explain why both indentical and non-identical twins are used in investigations (2) | Identical twins show genetic influence/differences Non-identical twins also show an environmental/non-genetic influence |
Explain why it is an advantage to apply the treatment (i.e. 250 seeds per m2) to each row and each column (2) | Different envrionment or different variables in field Minimises the effect of variables |
An investigation to determine whether pH affects the rate of an enzyme controlled reaction. Write a null hypothesis. | There is no significant difference between the rate at which the enzyme works at different pHs |
Name 3 statistical tests | Standard error and 95% confidence limits Chi-squared test Spearman rank correlation |
When should you use standard error and 95% confidence limits? | When testing for a difference between 2 sets of data The data is continuous and means can be calculated "looking for significant differences (between mean values)" |
When should you use chi-squared test? | When testing for a difference between 2 sets of data The data is in discrete categories |
When should you use spearman's rank correlation test? | When testing for a correlation between 2 sets of data |
For correlation coefficient: Calculated value is than the critcal value so __ null hypothesis | Calculated value is greater than the critcal value so reject null hypothesis Calculated value is less than the critcal value so accept null hypothesis |
For correlation coefficient: Why do we reject the null hypothesis when the calculated value is greater than the critical value? | A probability of less than 0.05 or 5% that the correlation in results is due to chance |
For correlation coefficient: Why do we accept the null hypothesis when the calculated value is less than the critical value? | A probability of more than 0.05 or 5% that the correlation in results occurred due to chance |
Chi-squared Test: When do we reject our null hypothesis? | When our calculated value of Chi-squared is greater than the critical value of Chi-squared |
Chi-squared Test: When do we accept our null hypothesis? | When our calculated value of Chi-squared is less than the critical value of Chi-squared |
Why do we reject our null hypothesis when our calculated value of Chi-squared is greater than the critical value of Chi-squared? | ∵ there's less than 5% probability that the differences between the observed and expected data are due to chance |
Why do we accept our null hypothesis when our calculated value of Chi-squared is less than the critical value of Chi-squared? | ∵ there's more than 5% probability that the differences between the observed and expected data are due to chance |
Give the reason why logarithmic scales have been used on the y-axes in the graph | large range of values/numbers |
Scientists found a postive correlation between the inhibition of germination and the concentration of the extract. Describe how they could find out whether this correlation was significant. (3) | Produce null hypothesis Carry out Spearman Rank correlation test / find correlation coefficient Use values to show P \< critical value / find probability of results being due to chance |
What does the histogram indicate about the inheritance of this feature? Explain your answer. (2) | polygenic inheritance / several genes many categories / continuous range / single or multiple allele inheritance would produce discrete categories |
The standard error of the mean was calculated. What information would this give about the mean height of 17-year-old males? (2) | (SE gives idea of) variability of mean time / population mean would lie within these limits in 68% / 70% / 2 / 3 of samples |
Explain why the means and standard deviations are more useful than the ranges for detecting any differences between two samples (3) | Range = just extreme values / outliers OR not typical / not representative / could be anomalies Mean and SD uses all the values or less affected by anomalies Mean and SD can be used in a statistical test OR can be used to see if two results differ significantly |