Null-hypothesis for a One-Way Analysis of Covariance (ANCOVA)

Conceptual Explanation

With hypothesis testing we are setting up a null-hypothesis – the probability that there is no effect or relationship – and then we collect evidence that leads us to either accept or reject that null hypothesis.

As you may recall, a One-Way ANCOVA attempts to compare the influence of one independent variable with at least two levels (e.g., 1. Player – Football1, B-Ball2, Soccer3,) on a dependent variable (e.g., pizza slices consumed in one sitting) . . .

As you may recall, a One-Way ANCOVA attempts to compare the influence of one independent variable with at least two levels (e.g., 1. Player – Football1, B-Ball2, Soccer3,) on a dependent variable (e.g., pizza slices consumed in one sitting) . . .

. . . eliminating the effect of another independent variable (a covariate in this case) with at least two levels (e.g., gender)

Here is a template for writing a null-hypothesis for a One-Way ANCOVA:

Here is a template for writing a null-hypothesis for a One-Way ANCOVA:

There is no significant effect of [insert independent variable] on [insert dependent variable] controlling

for [insert covariate].

Example #1

A pizza café owner wants to know which high school athletes eat more pizza during their lunch break so she knows which group to advertise more to. Is it football, basketball, or soccer players? She further would like find out if there is still effect after controlling for age.

A pizza café owner wants to know which high school athletes eat more pizza during their lunch break so she knows which group to advertise more to. Is it football, basketball, or soccer players? She further would like find out if there is still effect after controlling for age. Template:

There is no significant effect of [insert independent variable] on [insert dependent variable] controlling

for [insert covariate].

A pizza café owner wants to know which high school athletes eat more pizza during their lunch break so she knows which group to advertise more to. Is it football, basketball, or soccer players? She further would like find out if there is still effect after controlling for age. Template:

Null-hypothesis:There is no significant effect of athlete type on number of pizza slices consumed in one sitting controlling for age.

There is no significant effect of [insert independent variable] on [insert dependent variable] controlling

for [insert covariate].

Example #2

A pastor of a congregation wants to know the degree to which his parishioners report applying his messages to their lives. He administers a survey. He decides he would like to see what the results would be if he were to take length of church attendance out of the equation.

A pastor of a congregation wants to know the degree to which his parishioners report applying his messages to their lives. He administers a survey. He decides he would like to see what the results would be if he were to take length of church attendance out of the equation.Template:

There is no significant effect of [insert independent variable] on [insert dependent variable] controlling

for [insert covariate].

A pastor of a congregation wants to know the degree to which his parishioners reporting applying his messages to their lives. He administers a survey. He decides he would like to see what the results would be if he were to take length of church attendance out of the equation.Template:

Null-hypothesis: There is no significant effect of the new teaching technique on parishioners reporting an internalization of the message controlling for sermon fatigue.

There is no significant effect of [insert independent variable] on [insert dependent variable] controlling

for [insert covariate].