Hypothetico-Deductive Process in Scientific Research

Types of Hypotheses

Scientific hypotheses are tentative explanations for observations. Statistical hypotheses include null (H0) and alternative (Ha) hypotheses.

Null Hypothesis

States no difference between compared groups. Example: H0 - No difference in feather pigmentation between flamingos supplemented with crustaceans versus those that are not.

Alternative Hypothesis

States a difference between compared groups. Example: Ha - Difference in feather pigmentation between flamingos supplemented with crustaceans versus those that are not.

Two-tailed Hypothesis

Considers differences in both directions. Example: Ha - Difference in feather pigmentation across diets.

One-tailed Hypothesis

Considers differences in one direction. Example: Ha - Flamingos fed a crustacean diet express more feather pigments than those fed a fish diet.

Predictions

Statements about expected outcomes in an experiment. Example: Expect to see a difference in color pigmentation based on diet.

Test with Experiment/Study

Conducting experiments to test predictions and hypotheses, ensuring controls, replicates, and randomization.

Collect the Data

Gathering data on dependent and independent variables to analyze.

Descriptive Statistics

Stats like the mean that describe data but cannot be generalized beyond the dataset.

Inferential Statistics

Stats like t-tests that allow making inferences about populations beyond the data.

Two-sample t-test

Used to determine if the mean scores are different across groups, involving t-calculated and critical t-value calculations.

Degrees of Freedom (df)

Calculated as n1 + n2 - 2, where n1 and n2 are sample sizes.

Critical t-value

A value from a table used to determine significance in a t-test.

Student's t Distribution

Distribution used in t-tests, where choosing an alpha of 5% leads to a 5% chance of rejecting H0 due to chance alone.

Type I error (false positive)

Probability of rejecting the null hypothesis although it is true

Scientific method in action

ask a question, integrate and synthesize info, establish hypothesis, articulate predictions, test, collect and organize data, analyze, interpret, communicate findings

One-sample t-test

Statistical test comparing the mean of a single sample to a known value or mean

Dependent variable

Variable whose value depends on another variable

Independent variable

Variable that stands alone and is not changed by the other variables you are trying to measure

p-value

Probability of obtaining test results at least as extreme as the results observed during the test, assuming that the null hypothesis is correct

Critical value (alpha)

The threshold value used to determine whether the null hypothesis is rejected

Type II error

Probability of not rejecting the null hypothesis although it is false

Scientific hypothesis

A proposed explanation for a phenomenon based on observations and scientific knowledge

Statistical hypothesis

A statement about the relationship between two or more variables in a population

Null hypothesis

A general statement that there is no relationship between two measured phenomena

Alternative hypothesis

A hypothesis that states there is a significant difference or relationship between two variables

One-tailed t-test

A statistical test in which the critical area of a distribution is one-sided

Two-tailed t-test

A statistical test in which the critical area of a distribution is two-sided and tests for differences in both directions

Dependent vs. Independent variable

Dependent variable changes in response to the independent variable, which is not influenced by other variables

t-statistic

A measure that quantifies the difference between the sample mean and the null hypothesis mean in terms of the sample standard deviation

Variance

A measure of the dispersion of a set of data points around their mean value

Standard deviation

A measure of the amount of variation or dispersion of a set of values

experimental design components

randomization, control, and replication

a

when a = 0.05 there is a 5% chance of rejecting a true null hypothesis

level of significance

the max probability of committing a type 1 error and is symbolized by a

d = 1-B

power of the test statistic