Introduction to lab data Stickrath What does mean

Introduction to lab data Stickrath

What does “mean” mean? • Click on the link below…be sure you read about the following terms: mean, median, mode, range • http: //math. about. com/od/statistics/a/Mean Median. htm

Why are “trend lines” trendy? • Click on the link below • http: //www. visionlearning. com/library/mod ule_viewer. php? mid=109

How can “error bars” be erroneous? • Error bars may show standard errors (SE), or standard deviations (SD). • Different types of error bars give quite different information. • Descriptive error bars. Range and standard deviation (SD) are used for descriptive error bars because they show the data are spread. – Range error bars encompass the lowest and highest values. – SD error bars are calculated using the SD equation • SD = √[(sum of each value – mean)2/n] • Inferential error bars. In experimental biology it is more common to be interested in comparing samples from two groups, to see if they are different. – Standard Error (SE) is defined as SE = SD/√n.

Rules for Error Bars • Rule 1: when showing error bars, always describe in the figure legends what they are. • Rule 2: the value of n (i. e. the sample size) must be stated in the figure legend. • Rule 3: because experimental biologists are usually trying to compare experimental results with controls, it is usually appropriate to show inferential error bars, such as SE, rather than SD. However, if n is very small (for example n = 3), rather than showing error bars and statistics, it is better to simply plot the individual data points.

• What can you conclude when standard error bars do not overlap? – When standard error (SE) bars do not overlap, you cannot be sure that the difference between two means is statistically significant. Even though the error bars do not overlap in experiment 1, the difference is not statistically significant. – You must use a t-test or chi-square test to compare data • What can you conclude when standard error bars do overlap? – When SE bars overlap, (as in experiment 2) you can be sure the difference between the two means is not statistically significant