Intelligence Survey Method

When one speaks of intelligence or how bright another person is, the often quoted figure is the IQ or intelligence quotient. It is the most often used standard of how smart a person is. This paper shall look at what intelligence tests measure, how the IQ tests measure intelligence and interrogate their history. It shall then apply the tests to school policy and hence evaluate their validity.

The student data file was used as the data source. The sample size included one hundred men and one hundred women. Thirty-five out of one hundred men had not declared for a degree. Fifteen out of one hundred women had not declared for a degree. The level of

Then comparing the level of school years completed with the sex, female (N=69360) and male (N=67406), another significant relation was found t (136764) = 6.62 (0.15). The level of school years completed has a relationship with sex (see appendix F). Therefore, we reject the null hypotheses.

There is a copious amount of advantages and disadvantages associated with this proposition of a standardized IQ test granting entry to third level education institutions. From the research I have carried out, I found many theories of intelligence and intelligence assessment, which convey the various advantages and disadvantages associated with this proposition. In my opinion, and from the research and reading I have carried out, I find the ‘standardized IQ test’ to be slightly too general to be used.

There are a variety of topics that are interesting in life. This interest may then become a point of inquisition, where an individual may formulate a relationship between two variables, which may or may not influence each other. Next, a hypothesis is formed and tested. In this same manner, a school educator was interested in determining the potential relationship between grade point average (GPA) and IQ scores among ninth graders. The educator random sampled 30 ninth graders, ages 14 years old and administered the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV). This writer will be expanding further on this topic and will formulate the null and alternative hypothesis, describe the four scales of measurement, describe whether if there is a correlation significant (positive, negative, or no correlation) enough between both variables, describe the strength of the relationship, describe what the results reveals about the hypothesis, and what conclusions can be drawn from the results.

In the earlier year of psychology and research there had been ways on how to calculate different subjects that would be used to portray the demographics of social groups. One of which is intelligence testing. Looking back in the history of intelligence testing, there had been many studies conducted on intelligence that indicated some strong theories on what determines intelligence. The most controversial involving race and ethnicity. Modern research has made much advancements to say that these researchers did not realize was that there was much flaw in their procedures. Not to mention that the obliviousness may have been a result of subjectivity. These claims can be invalidated by many studies with revealing the

Gustave obtained a FSIQ standard score of 89 (23rd percentile) and falls within the Low Average range. His performance across the various indexes ranged from the Low Average to Average. His intelligence is best understood by his performance on the separate indexes. Therefore, an analysis of the various subtest scores needs to be taken into consideration in assessing Gustave’s ability to function and learn successfully in the educational setting due to variability within the domains.

The use of methodology is Primary data which includes Questionnaire. Apart with the Primary data collection, the paper is based on the information retrieved from the internet via journals, e-books and websites. The data has been presented with the use of bar diagrams and pie charts. Results and recommendations have been derived which are discussed further in this research paper.

For this data set, the student t-test is best to be used in testing the hypothesis. Here, two tailed-sample tests would be used at a level of significance of 5%. This will help us to pick an alpha at 0.25 in each tail to test the direction, which the test statistic is significant(LAWRANCE, 1987, p. 280). The relationship in both directions is significantly tested by our hypothesis which will compare the mean of the given sample population to the given value x obtained by the t-test. We shall then use the obtained p-value to make a decision whether to accept or reject our null hypothesis.

Most of the students were in their second year of study. The sample included 186 students, with approximately 60% female and 40% male. The mean age of the sample was 19.5 ± 1.54 years.

These participants were between the ages 16 and 17. This sample has many limitations including the small sample size, age bias, gender bias and school bias. Due to these limitations the investigation lacks validity and therefore does not reflect the wider population. In order to improve the sample size random allocation should occur in order to obtain equal gender, a wide variety of ages and from different schools and areas. The sample needs to be larger as it is too small and does not provide valid responses. Sample size is important in order to gain validity and improve the overall

In Table 3, the Rotated Component Matrix reports the factor loadings for each variable. Variable scores that were high and significant are highlighted. Four factors of SNSs usage has been identified :

Intellectual assessment and intelligence testing refer to the evolution of an individual’s general intellectual functioning and cognitive abilities (Samuel 2004) and also these assessments are de developed using standard procedures where the scores are recorded for the purpose of measuring achievement and compare the results with others in the society (Bordanora, 2001). Some authors stated that the inaccuracy of standard assessment results are caused by cultural bias (Klenowski 2009, Laros & Tellegen 2004, Bernhard 2000 and Schellenberg 2004). Also others taken into considering developmental factors of this issue (McCauley 2004). Comparison of the study, issues and research are most likely to convince cultural bias of the outcomes. Rest of

In general, there are several methods for data collection and the different data collection methods provided its own advantages and disadvantages (Sekaran 2003, p. 223). For carrying out the data collection, the appropriate methods should be applied. In the research, the data collection could be done through the interview, for example, face-to-face and telephone interview. To collect the data by using interview technique, the questionnaire is commonly employed as the instrument for gathering data, the questionnaire could be able to distribute by mail or electronic mail. In addition, the data collection could be conducted by observation of individuals with or without audio or video recording. Before choosing the methods for data collection the expertise of the researcher, the degree of accuracy required, time and resources must be taken into consideration. Thus,

The sample was drawn from 33 rural and urban schools. The target sample consisted of 3000 Children from rural schools and 1000 from urban schools. The mean, S.D., t-test and co-efficient of correlation was used for arriving at conclusions. The hypothesis of the study framed were, there is no significant sex difference in the academic achievement of primary school children, there is no rural urban difference in academic achievement of primary school children. The findings of the study points out that, Socio-economic status is positively and significantly co related with academic achievement at the primary stage of education, Higher SES category students show significantly better academic achievements in comparison to meddler low SES