Topic 0: Biology Review & Introduction to Statistics

AP Biology

Scientific Method

A step-by-step process used by scientists to investigate questions

Experimental group

Group that receives the experimental treatment (IV)

Independent Variable

One factor being changed between groups; the manipulated variable; graphed on the x-axis

Dependent Variable

Factor that is measured and affected by the IV; graphed on the y-axis

Constant

(Controlled variables) Factors kept consistent for all groups, ensuring only the IV affects the outcome

Statistics

Methods used to collect, process, or interpret quantitative data; helps us understand important information

Descriptive statistics

Methods used to summarize or describe observations/samples; includes measures of central tendency and measures of variability

Inferential statistics

Using observations to make estimates or predictions; generalizing a sample to a wider population; includes SEM, confidence intervals, and hypotheses tests

Central tendencies

Measures in descriptive statistics including mean, median, and mode that describe the center of a dataset

Mean

The average of the data set; sensitive to outliers

Median

The middle number in a range of data points

Mode

The value that appears most often; useful for categorical data

Variability

The degree to which data are spread out in a data set; helps give a more complete summary of a distribution

Range

The difference between the largest and smallest values in a data set.

Standard deviation

The average amount by which all the values deviate from the mean; measures the spread of data

Standard error

Used to assess how accurately the sample mean estimates the population mean

Chi-Square

A form of statistical analysis used to compare the actual counts/frequencies observed with the expected counts/frequencies

What are the 6 general steps of the scientific method?

Making an observation (1), asking questions (2), forming a hypothesis (3), designing an experiment (4), collecting data (5), and drawing a conclusion (6).

How are hypotheses formulated?

By explaining the relationship between variables, acting as a testable explanation for an observation

What is the difference between null and alternative hypotheses? Do you always need both?

Null hypothesis states there is no effect or difference between groups of data, with observations being the result of chance; Alternative hypothesis states there is a relationship, effect, or difference between two groups of data due to a nonrandom cause; both hypotheses is necessary for providing a baseline of comparison which can be tested, supported, or refuted using statistical tests

How do researchers determine their independent and dependent variables? How are they often graphed (ie what is on the x-axis what is on the y-axis)?

Researchers determine their independent and dependent variable by choosing which factor (variable) is being changed in the experiment. The factor that is being manipulated is graphed on the x-axis and is the independent variable. While the factor that is being measured is graphed on the y-axis.

Are constants the same as controls? Why or why not?

Constants are not the same as controls. Constants are the factors in an experiment that are kept the same throughout, ensuring that the outcome is only affected by the independent variable; controls are used for comparison, helping to validate analysis and draw conclusions from experimental results

When should a positive control be used? When should a negative control be used?

A positive control should be used to ensure that an experimental setup can produce a known effect, providing a reference point for treatment exposure. A negative control should be used to ensure that there is no effect when there should be no effect in an experiment.

Describe central tendencies. Identify when each type of central tendency should be used.

Central tendencies are methods that summarize or describe observations and samples for the center of a dataset. The mean should be used in approximately normal distributions that don’t contain outliers. The median should be used in skewed distributions as it is less affected by outliers. The mode should be used when describing categorical data when looking for the most common outcome.

What is used to measure variability?

Variability is measured by range, standard deviation, variance, skewness, and quartiles.

Is data more reliable with low or high standard deviation? Why?

Data is more reliable with a low standard deviation, the data is closer to the mean. A lower (smaller) standard deviation means that there are less outliers, demonstrating consistency in data

Why do researchers use SEM?

Researchers use SEM (Standard error of the mean) to assess how accurately the sample mean estimates the population mean. SEM utilizes standard deviation of the sample, estimating population variation

If standard error bars overlap is the difference between the means significantly different? Why or why not?

Not significantly different; bars measure a range of values in which there is 95% confidence the true population mean will fall within. When overlapping, there is not a statistically significant difference and the observed differences are likely due to chance.

Null Hypothesis

A testable explanation for an observation that has no effect or no difference between the two groups of data; observations are the result of chance.

Alternative Hypothesis

A testable explanation for an observation that has a relationship/effect/difference between the two groups of data; observations due to a nonrandom cause.

Negative Control Group

Group not exposed to any treatment or exposed to a treatment known to have no effect.

Positive Control Group

Group that is exposed to the treatment and is known to have an effect.