biology4alevel600

1 In an experiment investigating the effect of one variable on another, the independent variable is the one that you change and the dependent variable is the one that you measure. All other variables should be controlled (kept constant).  2 The range of the independent variable is the spread from lowest to highest value. The interval is the distance between each value in the range.  3 Temperature can be kept constant or varied using a water bath. pH can be kept constant or varied using buffer solutions.  4 The accuracy of a measurement is how true it is. For example, an accurate measuring cylinder reads exactly 50 cm3  when it contains 50 cm 3  of liquid. c  5 The precision of a measuring instrument is how consistent it is in giving exactly the same reading for the same value.  6 The reliability of a set of measurements is the degree of trust that you can have in them. A reliable set of measurements are likely to be very similar if you are able to do t...

One of the questions in the exam is likely to involve drawing a specimen on a slide, using a microscope, or drawing from a photomicrograph (a photograph taking through a microscope). Making decisions about what to draw You might have to decide which part of a micrograph to draw. For example, there might be a micrograph of a leaf epidermis, and you are asked to draw two guard cells and four epidermal cells. It is really important that you do exactly as you are asked and choose an appropriate part of the micrograph. Producing a good drawing It is very important that you draw what you can see, not what you think you ought to see. Forexample, during your AS course you may have drawn a TS of a stem where the vascular bundles were arranged in a particular way, or were a particular shape. In the exam, you could be asked to draw a completely different type of vascular bundle that you have never seen before. Look very carefully and draw what you can see. Your drawing should: • be large and draw...

It is very important to understand the difference between experimental errors and 'mistakes'. A mistake is something that you do incorrectly, such as misreading the scale on a thermometer, or taking a reading at the wrong time, or not emptying a graduated pipette fully. Do not refer to these types of mistake when you are asked to comment on experimental errors. You've already seen, on post # 70  , that every measuring instrument has its own built-in degree of uncertainty in the values you read from it. You may remember that, in general, the size of the error is half the value of the smallest division on the scale. Errors can also occur if there were uncontrolled variables affecting your results. For example, if you were doing an investigation into the effect of leaf area on the rate of transpiration, and the temperature in the laboratory increased while you were doing your experiment, then you can't be sure that all the differences in rate of transpiration were entirely...

Once you have collected, tabulated and displayed your results, you can use them to draw a conclusion. When you are thinking about a conclusion, look right back to the start of your experiment where you were told (or you decided) what you were to investigate. For example: • In investigation 1, investigating the effect of temperature on the rate of breakdown of hydrogen peroxide by catalase, your conclusion should provide an answer to this question. • in investigation 2, investigating the effect of immersion in solutions of different sucrose concentration on the change in length of potato strips, your conclusion should state the relationship between the concentration of sucrose solution and the change in length of the potato strips. • in investigation 4, testing the hypothesis: the density of stomata on the lower surface of a leaf is greater than the density on the upper surface, your conclusion should say whether your results support or disprove this hypothesis. Explaining your reasonin...

When you have collected your data and completed your results table, you will generally want to display the data so that anyone looking at them can see any patterns. 1. Line graphs  Line graphs are used when both the independent variable and the dependent variable are continuous. This is the case for the potato strip data on the table below. The graph can help you to decide if there is a relationship between the independent variable and the dependent variable. This is what a line graph of these data might look like. Notice: • The independent variable goes on the x-axis, and the dependent variable goes on the y-axis. • Each axis is fully labelled with units. You can just copy the headings from the appropriate columns of your results table. • The scales on each axis should start at or just below your lowest reading, and go up to or just above your highest reading. Think carefully about whether you need to begin at 0 on either of the axes, or if there is no real reason to do this. • Th...

You will often need to construct a table in which to record your measurements, readings and other observations. It is always best to design and construct your results table  before  you begin your experiment, so that you can write your readings directly into it as you take them. Let's think about  investigation 2  again (investigating the effect of immersion in solutions of different sucrose concentration on the change in mass of potato strips). You've made your decisions about the range and intervals of the independent variable (concentration of solution) - you've decided to use six concentrations ranging   from 0.0 moldm -3  to 1.0 moldm -3 . Your dependent variable is the change in length of the potato strips, and you are going to find this by measuring the initial length and final length of each strip. These are the things you need to think about when design ing your results table: • The independent variable should be in the first column. • The rea...

You will often be asked to take measurements or readings. In biology, these are most likely to be length, mass, time, temperature or volume. You could be taking readings from a linear scale (for example, reading temperature on a thermometer, reading volume on a pipette, or reading length on a potometer tube). You could be reading values on a digital display, for example reading mass on a top pan balance or time on a digital timer. There are some special terms that are used to describe measurements, and the amount of trust you can put into them. It's easiest if we think about them in terms of a particular experiment, so let's concentrate on investigation 1: Investigating the effect of temperature on the rate of breakdown of hydrogen peroxide by catalase.   Look back at the the post #69  to remind yourself what is being measured. Validity This is about whether what you are measuring is what you actually intend to measure. For example, in investigation 1, does measuring the...

Many of the experiments that you will do during your AS course, and usually Question 1 in the examination paper, will investigate the effect of one factor on another. These factors are called variables . Types of variables The factor that you change or select is called the independent variable. The factor that is affected (and that you measure when you collect your results) is the dependent variable. The table shows some examples. Table 1 If you are investigating the effect of one variable on another, then you need to be sure that there are no other variables that might be affecting the results. It is important to identify these and - if possible - keep them constant. These are sometimes called control variables . Making decisions about the independent variable You may have to make your own decisions about the range and interval of the independent variable. Let's think about investigation 1 in the table above - investigating the effect of temperature on the rate of breakdown of h...