Loading presentation...

Present Remotely

Send the link below via email or IM


Present to your audience

Start remote presentation

  • Invited audience members will follow you as you navigate and present
  • People invited to a presentation do not need a Prezi account
  • This link expires 10 minutes after you close the presentation
  • A maximum of 30 users can follow your presentation
  • Learn more about this feature in our knowledge base article

Do you really want to delete this prezi?

Neither you, nor the coeditors you shared it with will be able to recover it again.


Some Dangers to Avoid in Drawing up Conclusions

Anito R Librando Xavier University High School

Anito Librando

on 21 November 2012

Comments (0)

Please log in to add your comment.

Report abuse

Transcript of Some Dangers to Avoid in Drawing up Conclusions

Some Dangers to
Avoid in Drawing
up Conclusions But before that... Does your summary appear similar to this?

This study was conducted with the purpose of determining the status of teaching science in the high schools of Province A. The descriptive method of research was utilized and the formative survey technique was used for gathering data. All the teachers handing science and a 20 percent representative sample of the students were the respondents. The inquiry was conducted during the school year 1989-1990. What about your findings?

Of the 59 teachers, 31 or 53.34 percent were BSE graduates and three or 5.08 percent where MA degree holders. The rest, 25 or 42.37 percent, were non-BSE baccalaureate degree holders with at least 18 education units. Less than half of all the teachers, only 27 or 45.76 percent were science majors and the majority, 32 or 54.24 percent were non-science majors. #1
The conclusion that can be drawn from the findings in No 2 under the summary of findings is this:

All the teachers were qualified to teach in the high school but the majority of them were not qualified to teach science. #2
How adequate are the facilities for the teaching of science?

And the findings show that the facilities are less than the needs of the students, the answer and conclusion should be“The facilities for the teaching of science are inadequate” #3
From the findings that the majority of the teachers were non-science major and the facilities were less than the needs of the students, what have been the factually learned are that the majority of the teacher were not qualified to teach science and science facilities were inadequate. It cannot be concluded that science teaching in the high schools of Province A was weak because there are no data telling that the science instruction was weak. The weakness of the science teaching is an indirect or implied effect of the non-qualification of the teachers and the inadequacy of the facilities. There are some PITFALLS to avoid! Researchers should not accept nor utilize quantitative data without question or analysis even if they are presented in authoritative forms. This is so because in some instances quantitative data are either inaccurate or misleading either unwittingly or by design. The data should be analyzed very critically to avoid misleading interpretations and conclusions. Bias Incorrect Generalization Incorrect
Deduction Incorrect
Comparison Abuse of Correlation of Data Misleading Impression Concerning Magnitude of Base Variable Business establishments, agencies, or organizations usually present or manipulate figures to their favor. We should be wary of the use of statistics in these cases because of the obvious profit motive behind. An individual may also do the same. A respondent to a questionnaire or in an interview may commit the same bias to protect his own interests. Hence, if there is a way of checking the veracity of presented data by investigation observation, or otherwise, this should be done to insure the accuracy of the conclusions based upon the data under consideration. An incorrect generalization is made when there is a limited body of information or when the sample is not representative of the population. The Alumni Association of a big university would like to conduct a survey to determine the average income of the alumni during their first ten years after graduation. Though the total number of returns may meet the sample size requirement, the population may not be properly represented by the actual composition of the sample. This is likely to happen because chances are that a great majority of the alumni in the high income bracket will respond readily but the great majority of those how are not doing well may ignore the survey by reason of pride. In such a case, the high income group is over represented and low income group is under represented in the sampling resulting in the overestimate of the average income of the entire alumni group. This is the result of a built-in sampling bias. This happens when a general rule is applied to a specific case. Suppose there is a finding that the science facilities in the high schools of Province A are inadequate. We cannot conclude at once that any particular tool or equipment is definitely inadequate. Suppose there is an oversupply of test tubes. Hence, to make the conclusion that all science equipment and tools in the high schools of Province A are inadequate is an incorrect deduction in this case. To conclude that School C is better equipped with microscopes than School D based on the number of microscopes owned by each school is incorrect comparison. A basic error in statistical work is to compare two things that are not really comparable. Suppose in the survey School C has been found to have 20 microscopes and School D only has eight. We may conclude immediately that School C is better equipped with microscopes than School D. However, upon further inquiry, School C has 1,500 students while School D has only 500 students. Hence, the ratio in School C is 75 students is to one microscope while in School D the ratio is 63 students to one microscope. Hence, School D is better equipped with microscopes than School C. A correlation study may show a high degree of association between two variables. In no case does correlation show causal relationship. When the government increases the price of gasoline, the prices of commodities also start to rise. We cannot conclude immediately that the increase in the price of gasoline is the sole cause of the increase in the prices of commodities. There are other causes to be considered such as shortage or under supply of the commodities, increased cost of production, panic buying, etc. Ratios can give erroneous impressions when they are used to express relationships between two variables of small magnitudes. A college announced that that 75% of its graduates passed the CPA examination at a certain time. Another college also advertised that 100% of its graduates who took the same examination passed. Actually, only four graduates from the first college took the CPA licensing examination and three happened to pass. In the second college, only one of its graduates took the examination and he happened to pass. To avoid making false impressions by making conclusions using ratios concerning variables of very small magnitudes, use the original data because the relationship is clear even without the use of a ratio. We may say that three out of the four graduates who took the CPA test passed.

One graduate who took the same test passed. Mr. Anito Ramas Librando Jr. Xavier University High School - Ateneo de Cagayan
English Department Reference:

Calderon, Jose F. and Gonzales Expectacion C. 1993.
"Methods of Research and Thesis Writing."
National Book Store, Inc., Mandaluyong City.
Full transcript