(chi-square) - We will be using the chapek9 data set on jamovi. Test the research hypothesis that,...
Question:
(chi-square) - We will be using the chapek9 data set on jamovi.
Test the research hypothesis that, robots prefer data and humans prefer puppies
(**note** start with adding the flowing filter: fx = choice != 'flower')
Data Analysis:
- Considering the RQ/RH: -- Does this research hypothesis suggest a symmetrical pattern of relationship, asymmetrical pattern of relationship or no relationship between these variables? Label the contingency table on the right and put in <, > or
- Examining the Contingency Table --
- Does the "pattern" in the table seem to support the RH:? Why or why not?
- Statistical analysis --
Number of robots number of data
Number of humans number of puppies
= df = p =
State the H0:
Retain or reject H0:
Support research hypothesis?
- Write-up the results
-- your turn
Test the research hypothesis that humans prefer flowers and robots prefer puppies.
(**note** remove old filter and use: fx = choice != 'data')
Data Analysis:
- Considering the RH: -- Does this research hypothesis suggest a symmetrical pattern of relationship, asymmetrical pattern of relationship or no relationship between these variables? Label the contingency table on the right and put in <, > or
- Examining the Contingency Table --
- Does the "pattern" in the table seem to support the RH:? Why or why not?
- Statistical analysis --
Number of robots number of flowers
Number of humans number of puppies
= df = p =
State the H0:
Retain or reject H0:
Support research hypothesis?
- Write-up the results
Walk through with Larger Contingency Tables
The purpose of the study was to examine the relationship between human/robot and choice preference (flower, puppy, or data). The researcher thinks that humans will prefer flowers and puppies more than data and that robots will prefer data over flowers and puppies. (**note** remember to remove the filter)
- What type of design is this?
Flower | Puppy | Data | |
Human | |||
Robot |
- Will the results be causally interpretable?
- Does this design have good initial equivalence? Why or why not?
- Is this study likely to have good ongoing equivalence? Why or why not?
Here are our results:
Contingency Tables | |||||||||
choice | |||||||||
species | puppy | flower | data | Total | |||||
robot | 13 | 30 | 44 | 87 | |||||
human | 15 | 13 | 65 | 93 | |||||
Total | 28 | 43 | 109 | 180 |
Tests | |||||||
Value | df | p | |||||
10.7 | 2 | 0.005 | |||||
N | 180 | ||||||
State the H0:
Retain or reject H0:
Support research hypothesis?
- Write-up the results