Factor analysis is a statistical technique used to uncover the structure (patterns or dimensions) of a set of observed variables, allowing factor analysts to break down the information into statistical groups. This paper uses factor analysis in Chapter I to examine factors predicting language development among first grade students. The database used provides data on several variables, such as reversal (syllable reversal), delonset (delete onset), judgtone (judgment of tone), learnword (morpheme learning), oddword (pick up the odd word in four choices), fillword (fill in a word in a sentence), and circleword (select the correct "root" for the word). Bivariate correlations are carried out to explain the need to perform the analysis and to better interpret the results obtained. A Principal Component Analysis with varimax rotation is applied as a data reduction and/or a structure detection method to ascertain how many different factors are needed to explain the pattern of relationships among the observed variables. In this analysis, two components were extracted. While the first factor accounted for nearly 34% of the variance in the original data, the second accounted for almost 18% of the variance, thereby demonstrating that these two factors together explained nearly 52% of the total variance. In the second Chapter, a summary of the most commonly used statistical tests employed in epidemiology and medical statistics are summarized. Chapter III concludes the paper.