Statistical Analysis

Statistical analysis is defined as the process by which quantitative data is collected, examined, summarized, manipulated, and interpreted to reveal its underlying relationships, patterns, trends, and causes. According to Cowan, statistical analysis entirely depends on good measurement. It is very true that statistical analysis will be worthless if good measurement does not exist practically. Psychologists find quantitative and qualitative data necessary in their attempts to fully understand the world in which they live (Brain, 2002). However, psychologists face a significant challenge while associating the world with the collected data which is usually represented mathematically. In the field of psychology good statistical analysis and measurement are achievable through careful consideration of ordinal, nominal, ratio, and interval measurement scales.   

      Ordinal measurement scale is the type of scale that enables a psychologist to measure the satisfaction of clients (Howell, 2007). For instance, a therapist can specify the feelings of his or her clients as very dissatisfied, fairly dissatisfied, fairly satisfied, or very satisfied. The therapist can therefore statically analyze the extent of client satisfaction during a therapeutic relationship. Nominal scale is defined as a measurement scale in which a psychologist uses labels or names for particular characteristics. For instance, a patient can be classified as suffering from psychosis or neurosis. Interval measurement scale is the type of scale in which intervals between different points on the same scale are equal. Psychologists treat some psychological measures such as Intelligence Quotient and neuroticism as interval scales. Ratio scale is applicable in the sign and rank dependent expected utility model to explain the observed behaviors as consistent or inconsistent.  

      Therefore, measurement scales are very crucial in the field of psychology because they enable psychologists to understand the world by statistically analyzing data. Good measurements as well as statistical analysis results are associated with the appropriate use of nominal, ordinal, interval, and ratio measurement scales. Psychological traits can be analyzed effectively by using the measurement scales. Statistical analysis is valuable when psychologists maintain good measurement.