Data Collection and Presentation | Statistics

Summary

This video delves into the crucial aspects of data collection and presentation in statistics. It distinguishes between primary and secondary data, detailing methods like direct experiments, interviews, surveys, and observations for gathering primary data. The script also emphasizes the importance of proper citation when using secondary data. For data presentation, it outlines textual, tabular, and graphical methods, including frequency distribution tables and various graphs like histograms, bar graphs, line graphs, and pie charts, to effectively communicate data insights.

Takeaways

• 🔍 Data collection is essential for statistics and involves gathering primary (first-hand) and secondary (existing) data.
• 🧪 Primary data collection methods include direct experiments, interviews, surveys, observations, and registrations.
• 📊 Tools for data collection can range from experiment logs and interview guides to attendance sheets.
• 📚 Secondary data is borrowed from other researchers and requires proper citation to credit the original source.
• ✍️ Data presentation involves transforming raw data into formats that are understandable and accessible to an audience.
• 📝 Textual presentation of data involves using narrative and paragraphs to describe the data.
• 📋 Tabular presentation, such as frequency distribution tables (FDT), organizes data into classes and frequencies for easy analysis.
• 📊 Graphical methods like histograms, bar graphs, line graphs, and pie charts provide visual representations of data for quick understanding.
• 📈 Histograms are used for quantitative data and show continuous data flow without gaps between bars.
• 📊 Bar graphs are suitable for categorical data, allowing gaps between bars to represent different categories.
• 📈 Line graphs, also known as time series, depict data trends over time, highlighting patterns and the steepness of data changes.
• 🍕 Pie charts illustrate the proportion of components that make up a whole, useful for showing parts of a total like sales or budget allocations.

Q & A

What are the two main types of data discussed in the video?

The two main types of data discussed in the video are primary data and secondary data. Primary data refers to data collected by the researchers themselves, while secondary data comes from other researchers, which may include published or unpublished materials.

What is an example of a tool used for collecting primary data through direct experiment?

An example of a tool used for collecting primary data through direct experiment is an experiment log or observation log, which is used to record observations and results during the experiment.

How is an interview guide defined in the context of the video?

An interview guide, as defined in the video, is an outline of the topics to be discussed with an interviewee. It may contain questions or simple topics that serve as the flow of the interview.

What is the purpose of a survey in data collection?

A survey is used for collecting primary data through self-administered questionnaires, which can be in the form of checklists or rating scales distributed to respondents to gather their perceptions or data.

Can you explain the process of creating a frequency distribution table (FDT) for qualitative data?

To create an FDT for qualitative data, list the different categories or responses in the first column as row headers, and then count the frequency or number of occurrences for each category, placing these counts in the corresponding row.

What are the common parts of a statistical table?

The common parts of a statistical table include the table number and title, column headers, row headers, and the body, which is the intersection of rows and columns containing the data.

How does a histogram differ from a bar graph in terms of data representation?

A histogram represents quantitative data and does not have gaps between the rectangles, showing a continuous flow of data. In contrast, a bar graph represents categorical or qualitative data and allows gaps between the bars, as these represent different categories.

What is the significance of the slope in a line graph?

The slope of a line graph indicates the rate of change in the data over time. A steep slope signifies a rapid increase or decrease, while a gentle slope indicates a slower change.

Why is a pie graph used for data presentation?

A pie graph is used to show how different components make up a whole. It is effective for displaying data that can be divided into subparts, such as the allocation of resources or the composition of sales.

What are the three main methods of data presentation mentioned in the video?

The three main methods of data presentation mentioned in the video are textual, tabular, and graphical methods. Textual is used for narratives, tabular for key points, and graphical for audience-friendly visual representations.

Outlines

00:00

📊 Introduction to Data Collection and Presentation

This paragraph introduces the topic of data collection and presentation, emphasizing the importance of data in statistics. It distinguishes between primary and secondary data, explaining that primary data is collected by the researcher, while secondary data is sourced from other researchers' work. Various methods and tools for collecting primary data are outlined, including direct experiments, interviews, surveys, observations, and registration. The paragraph also touches on the necessity of presenting raw data in a way that is understandable to the audience, hinting at different presentation formats to be discussed later.

05:01

📈 Presenting Data: Textual and Tabular Formats

The second paragraph delves into the presentation of data, starting with textual presentation where data is narrated through paragraphs and narrations. It provides an example of how to present data from a class test, detailing the scores and performance of students. The paragraph then transitions to tabular presentation, focusing on frequency distribution tables (FDT). It explains the structure of statistical tables, including table number, title, column headers, row headers, and the body containing the data. An example is given for creating a qualitative FDT for students' comfort food preferences, illustrating how to list categories, count frequencies, and calculate totals.

10:03

📊 Graphical Data Presentation: Histograms and Bar Graphs

This paragraph explores graphical methods of data presentation, beginning with histograms derived from quantitative frequency distribution tables. It describes the process of creating a histogram using age distribution data, emphasizing the need for continuous flow and no gaps between rectangles. The paragraph then contrasts histograms with bar graphs, which are used for categorical data and allow gaps between bars. It discusses the orientation of bar graphs, whether vertical or horizontal, and how they differ in axis representation. The paragraph also provides guidelines for interpreting histograms and bar graphs, such as looking for continuous data flow and the absence of gaps in histograms.

15:04

📉 Advanced Graphical Presentations: Line Graphs and Pie Charts

The final paragraph covers additional graphical data presentation methods, including line graphs and pie charts. It explains that line graphs, similar to histograms, do not touch the zero point on the y-axis and are used to display trends over time. The paragraph advises looking for patterns and noting the slope of the line to understand data behavior. Pie charts are introduced as a way to show how components make up a whole, with examples given for student allowance allocation and business sales components. The paragraph concludes by summarizing the different data presentation methods, highlighting the importance of choosing the right method to make data easily understandable for the audience.

Keywords

💡Data Collection

Data collection refers to the process of gathering and measuring information on variables of interest, which is essential for conducting research and analysis. In the video, data collection is discussed in the context of both primary and secondary data. Primary data is collected directly by researchers, often through methods like direct experiments, interviews, and surveys. Secondary data is obtained from existing sources, such as previously conducted research. The video emphasizes the importance of proper data collection as the foundation for accurate and meaningful data analysis.

💡Primary Data

Primary data is original information collected directly from the source, such as through experiments, surveys, or interviews. The video explains that primary data is authentic and first-hand, providing a direct insight into the subject of study. It is contrasted with secondary data, which is data that has been collected by others. Examples from the script include using experiment logs or observation logs in a laboratory setting to collect primary data.

💡Secondary Data

Secondary data consists of information that has been collected by others and is used for further analysis. The video discusses how secondary data can be obtained from published or unpublished materials, and it highlights the importance of proper citation to give credit to the original data owners. This type of data is valuable for researchers who may not have the resources to collect all data themselves.

💡Data Presentation

Data presentation involves the methods used to display data in a way that is clear, understandable, and engaging for the audience. The video covers various data presentation techniques, including textual, tabular, and graphical methods. The goal of data presentation is to make the data accessible and interpretable, allowing the audience to quickly grasp key insights and trends.

💡Textual Presentation

Textual presentation is a method of conveying data through written language, such as paragraphs and narratives. The video uses an example of describing student test scores in a class to illustrate textual presentation. This method is particularly useful for providing context and details that may not be as easily conveyed through tables or graphs.

💡Tabular Presentation

Tabular presentation organizes data into rows and columns within a table, making it easy to compare and analyze different variables. The video explains how to create a frequency distribution table (FDT) for both qualitative and quantitative data. This method is particularly useful for presenting data that can be categorized or counted.

💡Graphical Presentation

Graphical presentation uses visual representations, such as graphs and charts, to display data. The video discusses various types of graphs, including histograms, bar graphs, line graphs, and pie charts, each of which serves a different purpose in data visualization. Graphical presentation is highlighted as an audience-friendly method that allows for quick comprehension of data trends and patterns.

💡Histogram

A histogram is a type of graph that represents the distribution of a quantitative variable. The video describes how to create a histogram from a frequency distribution table, with examples showing age groups and their corresponding frequencies. Histograms are useful for visualizing the shape of the data's distribution, such as whether it is skewed to the left or right.

💡Bar Graph

A bar graph is a graphical representation of categorical data, where each bar represents a category and its length corresponds to the frequency or value of that category. The video distinguishes between vertical and horizontal bar graphs and explains that they are used to compare different categories. Bar graphs are mentioned in the context of showing the frequency of comfort food choices among students.

💡Line Graph

A line graph, also known as a time series graph, is used to display data points connected by straight lines, showing trends over time. The video describes how to interpret line graphs by looking for trends and the slope of the line, which indicates the rate of change. An example from the script includes a line graph showing the trend of student enrollment over several years.

💡Pie Chart

A pie chart is a circular graph that shows the relative proportions of parts to a whole. The video mentions pie charts as a way to represent data that can be divided into subparts, such as the allocation of a student's allowance or the components of a business's sales. Pie charts are effective for demonstrating the composition of a whole.

Highlights

Introduction to data collection and presentation in statistics.

Explanation of primary data as data collected by the researchers themselves.

Definition of secondary data as data obtained from other researchers' work.

Direct experiment as a method for collecting primary data with tools like experiment logs.

Interview as a method for primary data collection, using an interview guide as a tool.

Surveys as a self-administered method for collecting primary data through questionnaires.

Observation as a method for collecting primary data using checklists.

Registration as a simple method for collecting primary data, such as attendance sheets.

The necessity of proper citation when using secondary data from other researchers.

Raw data requires presentation methods to be understandable to an audience.

Textual presentation of data through narratives and descriptions.

Tabular presentation as a method for organizing data in tables with classes and frequencies.

Frequency Distribution Table (FDT) as a tool for organizing raw data.

Components of a statistical table including table number, title, column header, row header, and body.

Creating a qualitative FDT by listing categories and counting frequencies.

Quantitative data requires a different approach for constructing FDT, with a separate video provided for details.

Graphical methods as a visual way to present data for quick understanding.

Histogram as a graphical representation of quantitative data from FDT.

Bar graph as a graphical representation for categorical data with gaps between bars.

Line graph for showing trends over time with attention to patterns and slopes.

Pie graph as a way to represent parts of a whole, suitable for data that can be divided into subparts.

Summary of data presentation methods: textual, tabular, and graphical for different audience needs.

Transcripts

hello everyone in this video let us talk

about data collection and presentation

without further ado let's get this

lesson started

[Music]

data collection methods and tools of

course when we are talking about

statistics we are all dealing with data

data set the numbers that needs to be

interpreted

we cannot interpret something that we

have not yet collected so the following

are the different data and the methods

and tools on how we can collect them

when we talk about primary data based on

the previous video that i have presented

primary data refers to the data that the

researchers collected themselves these

are authentic first-hand data

and on the other hand we have secondary

data these are data that came from other

researchers

it may be from published or unpublished

materials

when we are dealing with primary data

the following are the methods and the

tools that we can use to collect them

first is by direct experiment say for

example we have different set up

in laboratories or in classroom

and we are observing and taking down

notes of the different results or

behavior of the things that we are

experimenting so what we can use as a

tool in experiment are the experiment

blogs or observation logs

another method of collecting primary

data is through interview it can be over

the phone or

through video conferencing or

face-to-face interview

and a tool can be the interview guide

when we say interview guide it is an

outline of the topic that you will be

discussing with your interviewee it may

contain questions or just simple topics

that will be the flow of the interview

next we have survey this is more of the

self-administered questionnaires

it can be in a form of checklist or

rating scales which you will distribute

to your respondents to get their

perception or to get data from them

observation say for example you are

seated

and

immersed in a certain setting and you

want to observe how the different

people interact with each other so you

can provide a checklist

and you will just put a check on the

things that you have noticed

and the most simple

way of

collecting primary data is through

registration for example you just want

to know how many students attended the

synchronous class so you can generate an

attendance sheet or a registration sheet

at the end or before the activity or

before the class

next secondary date as i mentioned a

while ago these are the data that

the other researchers

collected so when you are going to

borrow these data you have to

search no published and unpublished

materials

and you have to observe proper citation

to give credit to the original owner of

the data

data gathered are raw data they are not

yet ready to be presented to the

audience so you have to be familiar with

the different ways of presenting data

first and i think the very simple is the

textual presentation

from the word itself text while it is

presenting the data using paragraphs

narration

you are narrating the data gathered from

the respondents or the participants so

for example here in a class of 40

students five of them obtained the

perfect score of 50 in their third

quarter long test in statistics 18

students got a score of at least 40

while two students scored 19 and below

generally the students performed well in

the test with 30 or 75 of them obtaining

a passing score of at least 38 so that

is one good way to present the data

there are also other ways like tabular

form

from the word itself table or frequency

distribution table fdt

when we talk about fdt this is

organizing raw data in table using

different classes and frequencies when

we say classes it can be

qualitative or categorical

like

city or country where a person lives and

when we say frequency it is the number

of data

that is corresponding to a certain class

the count of the data

corresponding to the certain class

so the following are the common parts of

statistical tables

first part is the table number and title

when we say title it is a short phrase

that describes what the table is all

about and this part is found above the

table

column header it

talks about the label of each column

what does each column represent

row header is the label per row what is

that row referring to

and of course the body the body itself

is the intersection of a certain row and

a certain column that contains the data

we have different fdt depending upon the

nature of the data when we have a

categorical or nominal or qualitative

data something like this now 10 students

were asked regarding their comfort food

and the data below are their answers

we are tasked to find the frequency

distribution for the data so what we can

do to

create the fdt for this is we will just

list down the different comfort food

that will take up the first column

this is the column header for the first

column comfort food and the entries on

the first column will serve as the row

header

so we just list down all the possible

answers

and for the frequency we just count how

many students answered that comfort food

so for ice cream we have four that's why

we have four here

french fries we have two donuts we have

one and milk tea we have three so at the

end of the table of course we put the

total 10 students

and as you may notice the table also

contains the number in the title which

is found above it

that is how a qualitative or categorical

or nominal frequency distribution table

looks like

of course we know that aside from

qualitative data we also have

quantitative

data so in order to construct the fdt of

quantitative data i have made a separate

video and you can access it here in the

upper right corner you just click on

this link

i made a separate video about that

because it has certain steps that you

need to follow

the third

method of presenting data is the

graphical method when we talk about

graphs these are visual representations

that helps the audience or the viewers

understand the data at a single glance

so at first look they can get overview

of the data is the data increasing or

decreasing over time is the data

divided into different subparts those

are the important key points that the

data set may have and can be highlighted

by graphical representation

first we have the histogram histogram is

generated from

quantitative frequency distribution

table the one that has different class

boundaries so for example let's have an

excerpt of that fdt quantitative ftt let

us just take the columns that we need

which are the class boundaries and the

frequency let's make a histogram for

this

so this is actually the distribution for

the viewers ages

so you may notice we prepare

this blank

graph

for the y-axis we have the frequencies

and for the x-axis we have the

boundaries

we just write here the possible values

found in the class boundaries

first

is 19.5 to 29.5 that is 8

so we can draw a rectangle from 19.5

until 29.5 and its height should be 8

because that corresponds to the

frequency of that class for the next

class which is 29.5

until

39.5 its frequency is 9 that's why its

height should be 9.

for the next class 39.5 until 49.5

its frequency is 6 that's why its height

is until

6.

and finally we have 2

as the frequency or the height for 49.5

to 59.5

so the following are the things that you

have to take note when dealing with

histogram

first the histogram does not touch zero

the

leftmost part or leftmost line of the

histogram should not touch the

frequencies or the y-axis because it

will always start with

the lower class bounded here

second the histogram shows a continuous

flow of data or in other words there are

no gaps between the rectangles again let

me repeat that for histogram there

should be no gaps between the rectangles

because as you can see on the class

boundaries the data is also continuous

the first class ends with 29.5

and the second class starts with 29.5

so it seems like the ending point of the

first class

is the starting point of the next one

so that is for the histogram it's quite

similar to bar graph however bar graph

is dealing with categorical or

qualitative ftt

unlike in the histogram it deals with

quantitative fdt

since bar graph is derived from

qualitative or categorical fdt as you

may notice we have here the bars that

has gaps between them

yes bar graph allows gaps between the

rectangles because these are not

continuous data

different

bars refers to different categories

bar graph can either be

vertically oriented like this one

frequency of comfort food

it can also be horizontally oriented

just like the bar graph on the right the

first quarter sales by sales person in

us dollars

depending upon what is more appropriate

with the data set you can either use the

horizontal or the vertical bar graph

of course when we are dealing with

vertical bar graph the y-axis are the

frequencies

and the x-axis are the different

categories

the access will be switched

if we are dealing with a horizontal bar

graph

the y-axis will now be the categories

and

the x-axis will now be the sales or the

frequency

another type of graphical data

presentation is line graph or time

series

just like histogram line graph does not

touch any number on the y-axis or the

zero part because it starts with the

first entry which is the year

also line graph talks about the trend of

data over time how the different values

behave over time when you are presented

with a time series or line graph

the following are the things that you

have to look

first

look for trends or pattern

is the line decreasing or increasing

well of course it has something to do

with the behavior of the data if the

line is decreasing meaning the data is

also decreasing

or if the line is rising to the right

then the data is also increasing

another thing that you have to take note

is the slope of the line or the

steepness of the line

a steep slope

talks about a rapid decrease or increase

of the data set

just like what you can see in this line

graph or time series

from 2016 to 2017 it's decreasing but

not that rapid because the slope is not

that steep

there was

a rapid decrease

from 2017 to 2018

then it again increased from 2018 to

2019 and there was also a sudden drop

of enrollees from 2019 to 2020

so again for line graph or time series

look for pattern and take note of the

slope of the line

finally we have pie graph pie graph

talks about the components and how they

make up the whole like what we can see

in this pie graph

so 30

of the students shows milk tea as the

comfort food 40 chose ice cream

uh 20 chose french fries and 10

shows donut so always remember that pie

graph is used if the data can be divided

into different subparts for example the

allocation of allowance of a certain

student

how much does he allocate for food how

much

does he allocate for

mobile plan

for transportation

another pie graph can be about the

components of sales of a certain

business

how much of the sales came from a

certain business how much came from

investment and so on

so those are the different ways on how

we can present data

we have textual which is used more for

narratives

we have tabular if we need to look at

key points

that needs to be reported as well and

third presentation is the graphical

method which is more audience friendly

because

the viewers can understand the data at a

single glance

[Music]