Standard deviation is a measure of how much a value varies from the mean of the dataset. Here are the steps to calculating the standard deviation of a dataset:
Find the mean of the dataset
Subtract the mean from each data point and square the result
Find the average of the squared differences
Take the square root of that average
These calculation can be done through excel or google sheets. Click on the button below to watch a tutorial on using google sheets to calculate mean and standard deviation!
The standard deviation should be added to graphs representing your data. Follow the tutorial below to learn how to add Standard deviation in the form of error bars to your graphs!
Notes:
Use google sheets or excel to conduct statistical analysis!
Significance refers to the likelihood that observed relationships in the data are not due to random chances but are instead meaningful or significant
Here is a link to help determine what statistical analysis to use: https://www.scribbr.com/statistics/statistical-tests/
Chi-Square test is used to determine if there is a significant association with one or two categorical variables. There are two types of Chi-Square tests:
Chi-Square Goodness of Fit Test - Determines if the observed matches the expected frequencies for one variable
Ex. Determining if the bags of candy have the same number of pieces
Chi-Square Test of Independence - Determine if two variables might be related
Ex. Determining if there is a correlation between ice-creams bought and the weather on that day
Watch the tutorial linked below to learn how to complete Chi-Square on google sheets/excel:
Analysis of Variance (ANOVA) is used to measure the significance between the means of two or more groups/treatments. It compares the variation between groups to the variation within the group to determine if the data is significant.
One-Way ANOVA - Is used when there is one independent variable with multiple levels
Ex. Comparing the growth of a plant between no water, 1L of water, and 10L of water
Two-Way ANOVA - Is used when there are two independent variables to assess how they affect the dependent variable together
Ex. Examining the impact of sunlight (no light, light) and water (no water, 1L of water, 10L of water) on plant growth
Watch the tutorials below to learn how to conduct ANOVA Tests on google sheets/excel!
Tukey's test is usually used in conjunction with ANOVA to identify the specific groups or treatments that differ significantly from each other. This is used when the null hypothesis is rejected in the ANOVA test.
A T-Test is used to determine if there is a significance between the means of two groups. If there is more than two groups use an ANOVA.
Here is some more information about T-Tests, the different types, and how to determine which test to conduct:
https://www.statisticshowto.com/probability-and-statistics/t-test/