Factor Analysis Paper

Running head: FACTOR ANALYSIS 1
Factor Analysis Paper
Student’s Name
Professor’s Name
Affiliation
Date

FACTOR ANALYSIS 2
Factor Analysis
Methodology
A 25-item questionnaire that is IPIP scale sensitive was used to capture the responses of Inuit children
aged between 9 and 12 years; A set of five questions was used to represent each of the big five personality
traits i.e. OCEAN. The term OCEAN refers to openness, conscientiousness, extraversion, agreeableness, and
neuroticism. The questions are randomly placed to ensure that the respondents do not offer biased answers that
distort the truthfulness of the information gathered. A 5-point Likert-scale is used to measure the responses
provided by the Inuit children. The response options are given on a scale of 1 (strongly disagree) to 5 (strongly
agree). The hypothesis being evaluated is that the questions given through the IPIP-25 questionnaire effectively
measure each of the big five personality traits in Inuit children aged 9 to 12 years. Therefore, factor analysis is
facet of data reduction that seeks to establish correlation between a set of variables in a data set. The correlation
between the variables can be explained by an overall outcome. For example, if there is correlation between five
questions in the same category, then it is expected that the association between the variables can be explained
by a given personality trait. And as a result, we are able to report that those five correlated questions are can be
used in a research situation to gather information about the underlying personality trait. Hence, the objective of
performing a factor analysis in this study is to ensure that each set of five questions measure the same
personality (Williams, et. al., 2010).
According to provisions in the IPIP scales the 25 question are categorized as followed with regard to the
specific personality trait they are hypothesized to measure: extraversion (4,6,14,20,25); neuroticism
(5,8,11,15,24); openness (3,9,10,21,23), agreeableness (1,7,12, 16,18) and conscientiousness (2,13, 17, 19,22).
The 25-IPIP questionnaire then used to gather data from 1,006 respondents (Inuit children aged between 9 years
and 12 years). The questionnaires were issued randomly to potential respondents to eliminate biasness and
thereby increase the reliability of the information collected. The data will be assessed in SPSS with regard to
principal component analysis, parallel analysis, and finally the factor analysis will be performed. The principal

FACTOR ANALYSIS 3
component analysis is meant to aid with segmentation of large datasets into small groups that provide sensible
information. With regard to the parallel analysis the “rawpar.sps” syntax will be used given 95% confidence
interval, 1006 individuals, and 500random matrices. The results will be presented in the result section of this
assessment. The discussion segment will discuss the various implications made by the findings with regard to
exhibition of the big five personality traits in Inuit children. Finally, the research conclusion will
document/summary the overall insight gathered through the assessment of previous studies, data analysis, and
discussion of results (Lopez & Whitehead, 2013).
Results
Principal Component Analysis using Scree Plot
With regard to principal component analysis we can look at the solution below and conclude that we are
expected to retain only 6 components out of the 25 given. It is clear when the cut off is or where the plot starts
to form a scree this takes place below an Eigen value of 1. In this unrotated factor analysis we see that the basis
for the selection of components was based on an Eigen value of 1 as well. We see that the remaining 19 values
cannot be considered because they are below the cutoff of greater than or equal to 1 Eigen value (Mishra, et al.,
2017).

FACTOR ANALYSIS 4
Parallel Analysis
From the table of raw data Eigen values, means, and percentiles, we are able to compare the rawa data to
the 95% confidence level values. If the raw data Eigen values are larger than the values given for 95%
confidence level then we will retain that root. From the tables we can see that the express Raw data≥ Perctil e
holds for the first five roots after which the express becomes Raw data< Perctil e. We can therefore state that the
number of relevant component will be 5. (Watkins, 2005) Looking at the scree plot presented below we can see
that the means and percentiles values are also include with the raw data Eigen values for a visual presentation of
the findings. The green line is the 50th percentile (mean) and the brownish-yellow line above it is the 95th
percentile (95% confidence level). Both lines intersect with the blue line of raw data Eigen values and we are
only to consider the components above the 50th and 95th percentiles. But more stress on values that are actually