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Statistical treatment in thesis writing

Communication Reasearch 1
S.Y. 2013- 2014
T.F 7:00am – 8:30am MCS
June 21, 2013



The learners are anticipated to:
a. Figure out what record treatment is about.
b. Choose their very own right statistics in analysing their data. c. Stick to the steps involving record treatment.
d. Interpret the information involving tabulation.
e. Provide solutions towards the drills.

II. Outline of Content:
A. Record management of data.
B. Management of Data and Distribution
C. Measures of Central Habits
a. Mean,
b. Median,
c. Mode.
D. Frequency and percentage.
E. Ranking Method.
F. Chi-Square Techniques.
G. T-Z Test
H. Drills.

III. References:
A. Research (Simplified Help guide to Thesis Writing)
* “Developing the study Design” pgs. 168- 178
B. Website: explorable.com/record-treatment-of-data C. Website: explorable.com/measures-of-central-inclination D. Website: https://en.wikipedia.org/wiki/Student’s_t-test E. Website: https://en.wikipedia.org/wiki/Analysis_of_variance

A. Record Management Of DATA:
Is important to make utilisation of the data within the right form. Raw data collection is just one facet of any experiment the business of information is every bit important to ensure that appropriate conclusions could be attracted. This is exactly what record management of data is about.

There are lots of techniques involved with statistics that treat data within the needed manner. Record management of information is crucial in all experiments, whether social, scientific or other form. Record management of data greatly depends upon the type of experiment and also the preferred derive from the experiment.

“For example, inside a survey concerning the election of the Mayor, parameters like age, gender, occupation, etc.

Statistical treatment in thesis writing of Variance

could be essential in influencing the individual’s decision to election for the candidate. And so the data must be treated during these reference frames.”

An essential facet of record management of information is the handling of errors. All experiments almost always produce errors and noise. Both systematic and random errors have to be considered.

With respect to the kind of experiment being performed, Type-I and kind-II errors should be handled. Fundamental essentials installments of false positives and false negatives which are vital that you understand and eliminate to make sense from caused by the experiment.


Attempting to classify data into generally known patterns is really a tremendous help and it is intricately associated with record management of data. It is because distributions like the normal probability distribution occur very generally anyway that they’re the actual distributions in many medical, social and physical experiments.

If confirmed sample size is proven to be normally distributed, then your record management of information is done affordably for that investigator because he would curently have lots of support theory within this aspect. Care ought to always be taken, however, to not assume all data to become normally distributed, and ought to always be confirmed with appropriate testing.

Record management of data also involves describing the information. The easiest method to do that is thru the measures of central habits like mean, median and mode.

These assist the investigator explain in a nutshell the way the data are concentrated. Range, uncertainty and standard deviation assistance to comprehend the distribution from the data. Therefore two distributions with similar mean might have extremely different standard deviation, which shows how good the information points are concentrated round the mean.

Record management of data is a vital facet of all experimentation today along with a thorough understanding is essential to conduct the best experiments with the proper inferences in the data.

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