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Biostatistics Year biostats plan 11C - Coggle Diagram
Biostatistics
Year biostats plan
11C
Variables
What is a variable: A variable is a characteristic in (of) an experiment that can be measured and classified.
Categorical: A Categorical variable is a variable that can not be quantified, and can be placed (caracterized) in a set group of categories.
Numerical: A Numerical variable is a variable that can be expressed numerically or be quantified.
Dependant: The dependent variables are the variables that change with respect to the independent variable.
Independant: The independent variable are the variables that do not change with respect to other variables.
Controled: The control or controled variables are those variables that can be manipulated by the experimenter (author).
Hypothesis in Biology
Null Hyporthesis
In biology, a null hypothesis (H₀) is a statement that says there is no effect or no difference in an experiment or study. It’s the default idea that nothing significant is happening — for example, “a new drug has no effect on plant growth compared to water.” Scientists test this hypothesis to see if the evidence is strong enough to reject it and support an alternative explanation.
Alternative Hypothesis
An alternative hypothesis (H₁ or Ha) is the statement that there is an effect or a difference — it’s what you propose might actually be true. For example, “the new drug increases plant growth compared to water.” If the experimental data show a significant result, scientists reject the null hypothesis in favor of the alternative.
Describing DATA
Mueasurments of central tendantcy
Mean
It is the average from all the values in a dataset. For calculating it, we sum all the data values, then we divided by the number of individuals, and the results is the mean.
Median
It is the middle value of a data set when all numbers are arranged in ascending or descending order.
Mode
Is the value that appers most frequently in a data set. It measures the frequency from values.
Measurements of dispersion
Variance
Is measures how spread out are the vlaues in a dataset. The higher this value is, the more dispersed the values are in the dataset. For calculating it we use the following formula:
Standar deviation
It also measures the dispersion of values in a dataset. It represents how spread out the data values are around the mean. For calcuating it we use the following formula:
Range
It also measures the dispersion of values in a dataset. Nevertheless, this one represents how far is the smallest value from the largest value.
