Data meaning & Tabulation
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This document discusses data, its meaning and types. It defines data as a systematic record of quantities that can be arranged into information when organized. Data is classified as either quantitative or qualitative. Quantitative data can be measured numerically while qualitative data describes attributes. Sources of data collection are also explained as either primary or secondary. Primary data is originally collected for a specific purpose, while secondary data has already been previously collected. Finally, the document introduces tabular presentation of data and its components, as well as different types of tables used.
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Research objective
Research Objective
Research is an organized investigation of a problem in which there is an attempt to gain solution to a problem.
To get right solution of a right problem, clearly defined objectives are very important.
Clearly defined objectives enlighten the way in which the researcher has to proceed.
What is Research Objective?
A research objective is a clear, concise, declarative statement, which provides direction to investigate the variables.
Generally research objective focus on the ways to measure the variables , such as to identify or describe them.
Sometime objectives are directed towards identifying the relationship or difference between two variables.
Research objective are the results sought by the researcher at the end of the research process, i.e. what the researcher will be able to achieve at the end of the research study.
The objectives of a research project summarize what is to be achieved by the study.
Objective should be closely related to the statement of the problem.
CHARACTERISTICS OF RESEARCH OBJECTIVES
Research objectives is a concrete statement describing what the research is trying to achieve. A well-worded objective will be SMART, i.e Specific, Measurable, Attainable, Realistic, & Time-bound.
Research objective should be Relevant, Feasible, Logical, Observable, Unequivocal & Measurable.
Objective is a purpose that can be reasonably achieved within the expected timeframe &with the available resources.
The objective or research project summarizes what is to be achieved by the study.
The research objectives are the specific accomplishment the researchers hopes to achieve by the study
The objective include obtaining answers to research questions or testing the research hypothesis.
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The formulation of research objectives will help researcher to:
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A research objective is a clear, concise, declarative statement, which provides direction to investigate the variables.
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Objective is a purpose that can be reasonably achieved within the expected timeframe &with the available resources.
The objective or research project summarizes what is to be achieved by the study.
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Avoid the collection of data which are not strictly necessary for understanding & solving problem that he or she has defined.
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Brief introduction to Data and its types.
There are different types of data in Statistics, that are collected, analysed, interpreted and presented. The data are the individual pieces of factual information recorded, and it is used for the purpose of the analysis process. The two processes of data analysis are interpretation and presentation. Statistics are the result of data analysis. Data classification and data handling are important processes as it involves a multitude of tags and labels to define the data, its integrity and confidentiality. In this article, we are going to discuss the different types of data in statistics in detail.
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Nominal data
Ordinal data
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Continuous data
Qualitative or Categorical Data
Qualitative data, also known as the categorical data, describes the data that fits into the categories. Qualitative data are not numerical. The categorical information involves categorical variables that describe the features such as a person’s gender, home town etc. Categorical measures are defined in terms of natural language specifications, but not in terms of numbers.
Sometimes categorical data can hold numerical values (quantitative value), but those values do not have a mathematical sense. Examples of the categorical data are birthdate, favourite sport, school postcode. Here, the birthdate and school postcode hold the quantitative value, but it does not give numerical meaning.
Nominal Data
Nominal data is one of the types of qualitative information which helps to label the variables without providing the numerical value. Nominal data is also called the nominal scale. It cannot be ordered and measured. But sometimes, the data can be qualitative and quantitative. Examples of nominal data are letters, symbols, words, gender etc.
The nominal data are examined using the grouping method. In this method, the data are grouped into categories, and then the frequency or the percentage of the data can be calculated. These data are visually represented using the pie charts.
Ordinal Data
Ordinal data/variable is a type of data that follows a natural order. The significant feature of the nominal data is that the difference between the data values is not determined. This variable is mostly found in surveys, finance, economics, questionnaires, and so on.
The ordinal data is commonly represented using a bar chart. These data are investigated and interpreted through many visualisation tools. The information may be expressed using tables in which each row in the table shows the distinct category.
Quantitative or Numerical Data
Quantitative data is also known as numerical data which represents the numerical value (i.e., how much, how often, how many). Numerical data gives information about the quantities of a specific thing. Some examples of numerical data are height, length, size, weight, and so on. The quantitative data can be classified into two different types based on the data
Chapter 7 Knowing Our Data
Data refers to raw information collected for research purposes, while statistics are numerical quantities calculated from the data. There are several key stages to statistical analysis: collection, organization, presentation, analysis and interpretation of data. Data can be classified as quantitative or qualitative depending on whether they are expressed numerically. Primary data are collected directly while secondary data are already available from other sources. Proper selection of the statistical unit of analysis is important for research.
DATA-COLLECTION.pptx
Data can come from internal or external sources and be collected as either primary or secondary data. Primary data is collected directly from first-hand experiences through methods like interviews, questionnaires, or observation and allows for targeted research but is more costly and time-consuming. Secondary data has already been collected for other purposes and can be quicker to obtain but does not directly address specific research questions and risks being outdated or inaccurate. Both types of data have merits and limitations depending on the research needs.
QTOR
The document discusses different types of data and methods for collecting data. It defines primary data as data collected directly by the researcher through methods such as surveys, interviews, and observations. Secondary data is defined as data that has already been published or collected indirectly from sources like books, journals, and government records. The advantages of primary data include greater accuracy and detail, while it disadvantages include the time and resources required to collect it. Secondary data is more convenient but requires evaluation of its relevance, accuracy, and sufficiency for the research problem. Different types of tables for organizing quantitative data are also described including simple, double, and manifold tables.
Methods of data collection
The document discusses methods of collecting data for research. It describes primary data collection methods like observation, interviewing, surveys, and experimentation which involve directly collecting unpublished data from original sources. Secondary data collection methods involve using already published data for research purposes and include sources like census reports, company annual reports, and reports from government departments and international organizations. Both primary and secondary data have advantages and limitations for research. The choice of data collection method depends on the specific needs and conditions of the study.
Methods of data collection
The document discusses methods of collecting data for research. It describes primary data collection methods like observation, interviewing, surveys, and experimentation which involve directly collecting unpublished data from original sources. Secondary data collection methods involve using already published data for research purposes and include sources like census reports, company annual reports, and reports from government departments and international organizations. Both primary and secondary data have advantages and limitations for research. The choice of data collection method depends on the specific needs and conditions of the study.
Statistics (All About Data)
References:
Agarwal, B. L. 2006. Basic Statistics. Revised Fourth
Edition. New Age International (P) Ltd.: New Delhi.
Broto, Antonio S. 2006. Statistics Made Simple.
National Book Store: Mandaluyong City.
Microsoft® Encarta® 2009. © 1993-2008 Microsoft
Corporation. All rights reserved.
Pennings, Paul, Keman, Hans, and Kleinnijenhuis, Jan
1999. Doing Research in Political Science: An
Introduction to Comparative Methods and Statistics. Sage: London.
data analysis ii.ppt
This document provides information on data analysis, including what it is, why it is important, and how to manage and prepare data for analysis. Data analysis is the process of sorting information from collected data in a research study. It converts data into information and knowledge, and explores relationships between variables. Managing data involves coding it as it is collected and categorizing it. When preparing data analysis, proper use of text, visuals, headings and subheadings is important. Language used to report findings should be impartial and show relationships rather than making unsupported claims.
Definition Of Statistics
1) Statistics is the study of collecting, organizing, analyzing, and drawing conclusions from data. It involves sampling, hypothesis testing, and using statistical tests tailored to measurement scales and hypothesis types.
2) Descriptive statistics describe and summarize data quantitatively, while inferential statistics allow generalizing from samples to populations through statistical testing and other methods.
3) The document discusses differences between statistics and statistical data, types of data, levels of measurement, sampling techniques, and uses of statistics.
Data Collection.pptx
This document discusses data and its classification. It defines data as information in raw or organized form that represents objects, ideas, categories, etc. It then discusses the following key points:
- Data is essential for research and statistical analysis. It can come from primary or secondary sources.
- Primary data is collected directly by the researcher through methods like surveys, observation, and experiments. Secondary data comes from previously published sources.
- There are four main types of data classification: geographical, chronological, quantitative, and qualitative. Geographical looks at location, chronological at time, quantitative at measurable characteristics, and qualitative at attributes that can't be measured.
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Data meaning & Tabulation
- 1. DATA : MEANING AND TABULATION By: Dr.Sangeeta Solanki
- 2. PC3-ASSESSMENT FOR LEARNING Unit IV Data: meaning and types, Tabulation of Data graphic representation, percentage Central Tendency – Mean, Median, Mode.
- 3. What is Data? Data can be defined as a systematic record of a particular quantity. It is the different values of that quantity represented together in a set. It is a collection of facts and figures to be used for a specific purpose such as a survey or analysis. When arranged in an organized form, can be called information.
- 7. Quantiative Data: ◦ These can be measured and not simply observed. ◦ They can be numerically represented, and calculations can be performed on them. ◦ For example, data on the number of students playing different sports from your class gives an estimate of how many of the total students play which sport. ◦ This information is numerical and can be classified as quantitative.
- 8. Qualitative Data: ◦ They represent some characteristics or attributes. ◦ They depict descriptions that may be observed but cannot be computed or calculated. ◦ For example, data on attributes such as intelligence, honesty, wisdom, cleanliness, and creativity collected using the students of your class a sample would be classified as qualitative. ◦ They are more exploratory than conclusive in nature.
- 11. Primary Data These are the data that are collected for the first time by an investigator for a specific purpose. Primary data are ‘pure’ in the sense that no statistical operations have been performed on the them They are original. An example of primary data is the Census of India.
- 12. Secondary Data They are the data that are sourced from someplace that has originally collected it. This means that this kind of data has already been collected by some researchers or investigators in the past and is available either in published or unpublished form. This information is impure as statistical operations may have been performed on them already. An example is an information available on the Government of India, Department of Finance’s website or in other repositories, books, journals, etc.
- 23. TYPES OF TABLE
- 24. TYPES OF TABLE
- 26. NEXT TOPIC