1. Data are measurements of variables from every individual or object under consideration.
Kinds of Data
Primary data – data obtained directly from the source of the information.
Secondary data– data obtained have been previously collected by another person or institution for some other purposes, taken usually from publications or existing records.

2. Methods of Data Collection
Experimental Method – data collected under controlled conditions
Observational Method – data collected by recording the behavior at the time of occurrence
Survey Method – data collected are provided by identified respondents either by personal interviews or by mailed questionnaires
Use of Existing Records – data collected from published materials like reports, personal files, historical records

3. Census or Complete Enumeration – the process of gathering information from every unit in the population.
Survey Sampling – process of obtaining information from the units in the selected sample
The government is conducting a census to know the population size of the country. Persons are assigned to go from house to house to asked how many persons lived there
A certain toothpaste company wants to know if the consumers are happy with the use of their product. A number of people were assigned to different supermarkets all over the Philippines to ask randomly those who are buying their product for their opinion.

4. Presenting Data with Text
- data or highlights of the data are incorporated to a paragraph or in a textual presentation
Advantages:
a) This presentation gives emphasis to significant figures and comparisons, usually highlighted in the text.
b) It is simplest and most appropriate approach when there are only a few numbers to be presented such as numerical measures that summarize the data.

5. - the systematic organization of data in rows and columns Advantages:
Disadvantages:
a) When a large mass of quantitative data is included in a text or paragraph, the presentation becomes almost incomprehensible.
b) Paragraphs can be tiresome to read especially if the same words are repeated so many times.
Presenting Data with Tables
- the systematic organization of data in rows and columns
Advantages:
a) more concise than textual presentation
b) easier to understand
c) facilitates comparison and analysis of relationship among different categories
d) presents data in greater detail than a graph
TABLE 1 Number, Percent Distribution, and Daily Average of Reported
Foreign Births by Sex and by Month of Occurrence: 2004
====================================================================
| | Sex
Month of | | Daily
Occurence Total | Percent | Average Male | Female
Total , , ,312
January
February
March
April
May
June
July
August
September
October
November
December

6. Guidelines in Constructing Tables
The title should be concise, written in telegraphic style, not in complete sentence.
2. Column labels should be precise. Stress differences rather than similarities between adjacent columns. As much as possible, two or more adjacent columns should not begin nor end with the same phrase. This is frequently a signal that a spanner head is needed.
3. The arrangement of lines in the stub depends on the nature of classification, purpose of presentation or limitations of space

7. 4. Categories should not overlap.
5. The units of measurements must be clearly stated.
6. Show any relevant total, subtotals, percentages, etc.
7. Indicate if data were taken from another publication by including a source note.
8. Tables should be self-explanatory, although they may be accompanied by a paragraph that will provide an interpretation or direct attention to important figures.

8. Frequency Distribution Table – tabular arrangement of data by grouping the values into mutually exclusive classes and showing the number of observations falling in each class.
Single-Value Grouping Frequency Distribution Table
form of frequency distribution where the distinct values are used as classes; commonly used for qualitative types of data.
Grouping by Class Intervals
- form of frequency distribution where mutually exclusive classes are in the form of intervals; used for quantitative types of data.

9. No. of accidents in a certain intersection No. Of Cars Frequency
Relative Frequency 2
0.14 1 5
0.36 4
0.29 3
0.07
Class Interval
Class Boundaries
Frequency F
Relative frequency
Class Mark x
7-9 2
0.04 8
10-12
0.16 11
13-15 14
0.28
16-18 19
0.38 17
19-21 7
0.14 20

10. Presenting Data with Graphs
A graph is a device for showing numerical values or relationships in pictorial form.
Advantages
a) main features and implications of a body of data can be grasped at a glance
b) can attract attention and hold the reader’s interest
c) simplifies concepts that would otherwise have been expressed in so many words
d) can readily clarify data, frequently bring out hidden facts and relationships

11. Qualities of a Good Graph
Accurate – should not be deceptive, distorted or misleading
b) Simple – should be straightforward, not loaded with irrelevant or trivial symbols and ornamentation
c) Clear – should be easily read and understood
d) Appearance – to attract and hold attention

12. Line Graph – useful for showing trends over a period of time
Types Of Graph
Line Graph – useful for showing trends over a period of time
Age at First Marriage

13. b) Bar Graph – consists of a series of rectangular bars where the length of the bar represents the magnitude to be demonstrated

14. c) Pie or Circle Graph – a circle is divided into sectors in such a way that the area of each sector is proportional to the size of the quantity represented by that sector
- useful in showing how a total quantity is distributed among a group of categories

15.                                                                                                                                                       
d) Pictogram – pictures or symbols are used to represent certain quantity or volume

16. e) Histogram – a bar graph of a frequency distribution table
- class boundaries are represented by the width of the bars and the frequencies that fall within the classes are represented by the height of the bars

17. Steps to construct a stem and leaf plot
f) Stem and Leaf Plots
Steps to construct a stem and leaf plot
Divide each measurement into two parts: the stem and the leaf.
List the stems in a column, with a vertical line to their right.
For each of the measurement, record the leaf portion in the same row as its corresponding stem.
Order the leaves from lowest to highest in each stem.
Provide the key to your stem and leaf coding so that the reader can recreate the actual measurements if necessary.
1 0
Leaf unit=1 8
9 0 5

18. g) Box plot A boxplot is a concise graph showing the five point summary. Multiple boxplots can be drawn side by side to compare more than one data set.

19. h) Map chart A map chart displays data by shading sections of a map, and must include a key. A total data number should be included.

20. Overall trends show well Needs limited categories
Pictograph A pictograph uses an icon to represent a quantity of data values in order to decrease the size of the graph. A key must be used to explain the icon.
Advantages
Easy to read
Visually appealing
Handles large data sets easily using keyed icons
Disadvantages
Hard to quantify partial icons
Icons must be of consistent size
Best for only 2-6 categories
Very simplistic
Map chart A map chart displays data by shading sections of a map, and must include a key. A total data number should be included.
Good visual appeal
Overall trends show well
Needs limited categories
No exact numerical values
Color key can skew visual interpretation
Pie chart A pie chart displays data as a percentage of the whole. Each pie section should have a label and percentage. A total data number should be included.
Shows percent of total for each category
No exact numerical data
Hard to compare 2 data sets
"Other" category can be a problem
Total unknown unless specified
Best for 3 to 7 categories
Use only with discrete data

21. Histogram A histogram displays continuous data in ordered columns
Histogram A histogram displays continuous data in ordered columns. Categories are of continuous measure such as time, inches, temperature, etc.
Histogram Explorer
Advantages
Visually strong
Can compare to normal curve
Usually vertical axis is a frequency count of items falling into each category
Disadvantages
Cannot read exact values because data is grouped into categories
More difficult to compare two data sets
Use only with continuous data
Bar graph A bar graph displays discrete data in separate columns. A double bar graph can be used to compare two data sets. Categories are considered unordered and can be rearranged alphabetically, by size, etc.
Can easily compare two or three data sets
Graph categories can be reordered to emphasize certain effects
Use only with discrete data
Line graph A line graph plots continuous data as points and then joins them with a line. Multiple data sets can be graphed together, but a key must be used.
Can compare multiple continuous data sets easily
Interim data can be inferred from graph line

22. Stem and Leaf Plot Stem and leaf plots record data values in rows, and can easily be made into a histogram. Large data sets can be accomodated by splitting stems.
Advantages
Concise representation of data
Shows range, minimum & maximum, gaps & clusters, and outliers easily
Can handle extremely large data sets
Disadvantages
Not visually appealing
Does not easily indicate measures of centrality for large data sets
Box plot A boxplot is a concise graph showing the five point summary. Multiple boxplots can be drawn side by side to compare more than one data set. More about boxplots here.
Shows 5-point summary and outliers
Easily compares two or more data sets
Handles extremely large data sets easily
Not as visually appealing as other graphs
Exact values not retained

23. Reasons for drawing a sample
Reduced cost
Greater speed
Greater scope
Greater accuracy
Necessity
Sampling is a process of selecting a subset of the population.
A sampling procedure that gives every element of the population a (known) nonzero chance of being selected in the sample is called probability sampling. Otherwise, the sampling procedure is called a non-probability sampling.

24. A representative sample is one that is similar in its characteristics to the population with which it was selected. The most effective way to obtain a representative sample is by randomization.
Randomization is a process of selecting elements of the population so that each element has a known, not necessarily equal, chance of being included in the sample.
Sampling frame is a list of elements of the population.

25. Some Probability Sampling Procedures
Simple Random Sampling (SRS)
Simple random sampling (SRS) is a method of selecting n units out of the N units in the population in such a way that every distinct sample of size n has an equal chance of being drawn. The process of selecting the sample must give an equal chance of selection to any one of the remaining elements in the population at any one of the n draws. A sample of size n is selected by generating n random numbers through the use of (1) chips of paper, (2) table of random numbers, and (3) random number generators in calculators.

26. Systematic Sampling
In systematic sampling, a sample is selected by taking at random an element in the population and every kth element thereafter, where k = N/n, rounded to the nearest integer.
Stratified Sampling
In stratified sampling, a ample is selected by taking independent random sample from each of the mutually exclusive subpopulations or strata of the population.
Cluster Sampling
In cluster sampling, a sample is selected by taking all or a subset of randomly chosen subpopulations or cluster.

27. Some Nonprobability Sampling Procedures
Convenience Sampling – selects sampling units that come on hand or are convenient to get information from
Purposive Sampling – sets out to make a sample agree with the profile of the population based on some pre-selected characteristic.
Quota Sampling – selects a specified number (quota) of sampling units possessing certain characteristics
Judgment Sampling – selects sample in accordance with an expert’s judgment