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The results of their statistical analyzes help you to understand the outcome of your study, eg. For example, whether a variable has an effect or not whether variables are related to whether differences between the observation groups are the same or different, etc., and so on are tools of science, no end to themselves. Statistics should be used to create their results Gringing and help you to tell objectively if you have significant results. In the reporting of statistical results that are relevant to your study, they therefore subordinate them the actual biological results.
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Reporting descriptive (summary) Statistics
Means: Always report the middle (average value) along with a measure of variability (standard deviation ( or the standard error of the average). Two common ways to express the mean and variability are shown below:
"Total length of the brown trout (n = 128) on average 34.4 cm (s = 12.4 cm) in May 1994, Samples from Sebago Lake. "
s = standard deviation (this format is preferred by Huth and others (1994)
"Total length of the brown trout (N = 128) on average of 34.4 ± 12.4 cm in May 1994, samples from Sebago Lake."
This style requires that it is specifically told in the methods which measure is reported for the variability with the mean.
When the summary statistics are displayed in graphical form (a figure), you can simply report the result in the text without to verbalize the summary values:
"mean total length of brown trout in Sebago Sea rose by 3.8 cm between May and September 1994 (Fig. 5)."
Frequencies: Frequency data should be summarized in the text with reasonable measures such as perme, proportions or conditions.
"During the case sales period, estimated 47% of brown trout and 24% of the brown trout were concentrated in the lowest parts of the lake (Table 3)."
Reporting results of the inferencing tests (hypothesis) tests
In this example, the key result is blue and the statistical result, which is found to be found, is red.
"The middle total length of the brown trout in the Sebago Sea rose significantly between May (34.4 ± 12.4 cm, n = 128) and September (38.2 ± 11.7 cm, n = 114) 1994 (Twomample T -Test, p. "
Note: Do not avoid writing whole sentences that simply say which test you have used to analyze a result, followed by another that analyzes the result. This wastes valuable words (economy !!) and increases unnecessarily the length of your paper.
Summary statistical test results in the figures
If the results shown in a figure have been tested with a inference test, it is appropriate to summarize the result of the test in the graph, so that you are so readers Can quickly grasp the meaning of the findings. It is imperative that you include information in your materials and methods or in the figure legend to explain how to interpret the coding system you use.
Multiple common methods for the summary of statistical results are displayed below.
Examples: Comparing groups (T tests, ANOVA, etc.)
Comparison of the means of 2 or more groups is usually displayed in a bar chart of the device and associated error rods .
Two groups can be applied to the greater mean value 1-4 to center the error bar via the error bar to display the relative level of the P value. In general "*" means P
The Asterisk can also be used with tabular results as shown below. Note how the author uses a footnote to define the p values ??that correspond to the number of Asterisks. (Courtesy of Shelley Ball)
For three or more groups, there are typically two systems: lines or letters.The system you use depends on how complicated it is to summarize the result. The first example shows a comparison of three means. The line, which spans two adjacent bars, indicates that they are not significantly different (based on a multiple comparison test), and since the line does not contain the pH 2, this means that the pH of pH 2 means From the pH 5.3 is significantly different (control) and the pH-3.5 group means. Note that information about interpreting the coding system (line or letters) are included in the figure legend.
If lines can not be easily pulled to summarize the result, the most common alternative is to use uppercase letters placed on the error bars. The shared letters between or between the groups would not specify a significant difference.
Example: Summary Correlation and Regression Analysis
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