### Abstract

There are many common misconceptions regarding factor analysis. For example, students do not know that vectors representing latent factors rotate in subject space, rather than in variable space. Consequently, eigenvectors are misunderstood as regression lines, and data points representing variables are misperceived as data points depicting observations. The topic of subject space is omitted by many statistics textbooks, and indeed it is a very difficult concept to illustrate. An animated tutorial was developed in an attempt to alleviate this problem. Since the target audience is intermediate statistics students who are familiar with regression, regression in variable space is used as an analogy to lead learners into factor analysis in the subject space. At the end we apply the Gabriel biplot to combine the two spaces. Findings from a textbook review, a survey, and a "think aloud" protocol were taken into account during the program development and are discussed here.

Original language | English (US) |
---|---|

Journal | Journal of Statistics Education |

Volume | 10 |

Issue number | 1 |

State | Published - Mar 2002 |

### Fingerprint

### Keywords

- Biplot
- Eigenvector
- Hypermedia
- Vector space

### ASJC Scopus subject areas

- Statistics and Probability
- Education

### Cite this

*Journal of Statistics Education*,

*10*(1).

**Teaching factor analysis in terms of variable space and subject space using multimedia visualization.** / Yu, Chong Ho; Andrews, Sandra; Winogard, David; Jannasch-Pennell, Angel; DiGangi, Samuel.

Research output: Contribution to journal › Article

*Journal of Statistics Education*, vol. 10, no. 1.

}

TY - JOUR

T1 - Teaching factor analysis in terms of variable space and subject space using multimedia visualization

AU - Yu, Chong Ho

AU - Andrews, Sandra

AU - Winogard, David

AU - Jannasch-Pennell, Angel

AU - DiGangi, Samuel

PY - 2002/3

Y1 - 2002/3

N2 - There are many common misconceptions regarding factor analysis. For example, students do not know that vectors representing latent factors rotate in subject space, rather than in variable space. Consequently, eigenvectors are misunderstood as regression lines, and data points representing variables are misperceived as data points depicting observations. The topic of subject space is omitted by many statistics textbooks, and indeed it is a very difficult concept to illustrate. An animated tutorial was developed in an attempt to alleviate this problem. Since the target audience is intermediate statistics students who are familiar with regression, regression in variable space is used as an analogy to lead learners into factor analysis in the subject space. At the end we apply the Gabriel biplot to combine the two spaces. Findings from a textbook review, a survey, and a "think aloud" protocol were taken into account during the program development and are discussed here.

AB - There are many common misconceptions regarding factor analysis. For example, students do not know that vectors representing latent factors rotate in subject space, rather than in variable space. Consequently, eigenvectors are misunderstood as regression lines, and data points representing variables are misperceived as data points depicting observations. The topic of subject space is omitted by many statistics textbooks, and indeed it is a very difficult concept to illustrate. An animated tutorial was developed in an attempt to alleviate this problem. Since the target audience is intermediate statistics students who are familiar with regression, regression in variable space is used as an analogy to lead learners into factor analysis in the subject space. At the end we apply the Gabriel biplot to combine the two spaces. Findings from a textbook review, a survey, and a "think aloud" protocol were taken into account during the program development and are discussed here.

KW - Biplot

KW - Eigenvector

KW - Hypermedia

KW - Vector space

UR - http://www.scopus.com/inward/record.url?scp=3042822099&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=3042822099&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:3042822099

VL - 10

JO - Journal of Statistics Education

JF - Journal of Statistics Education

SN - 1069-1898

IS - 1

ER -