The document discusses various statistical analysis methods and their purposes. It defines descriptive statistics as methods used to describe characteristics of a population or sample, such as measures of central tendency, dispersion, location, and distribution. Inferential statistics draw inferences from samples to make generalizations about populations. The document outlines specific descriptive and inferential statistical tests for both parametric and nonparametric data, and explains that the appropriate statistical method depends on the research problem and level of measurement used in a study.
Methods of data collection (research methodology)Muhammed Konari
Included all types of data collection.Includes primary data collection and secondary data collection. Described each and every classification of Data collections which are included in KTU Kerala.
In any single written message, one can count letters, words or sentences. One can categories phrases, describe the logical structure of expressions, ascertain associations, connotations, denotations, elocutionary forces, and one can also offer psychiatric, sociological, or political interpretations. All of these may be simultaneously valid. In short a message may convey a multitude of contents even to a single receiver.
Methods of data collection (research methodology)Muhammed Konari
Included all types of data collection.Includes primary data collection and secondary data collection. Described each and every classification of Data collections which are included in KTU Kerala.
In any single written message, one can count letters, words or sentences. One can categories phrases, describe the logical structure of expressions, ascertain associations, connotations, denotations, elocutionary forces, and one can also offer psychiatric, sociological, or political interpretations. All of these may be simultaneously valid. In short a message may convey a multitude of contents even to a single receiver.
Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making.
This was a presentation that was carried out in our research method class by our group. It will be useful for PHD and master students quantitative and qualitative method. It consist sample definition, purpose of sampling, stages in the selection of a sample, types of sampling in quantitative researches, types of sampling in qualitative researches, and ethical Considerations in Data Collection.
Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making.
This was a presentation that was carried out in our research method class by our group. It will be useful for PHD and master students quantitative and qualitative method. It consist sample definition, purpose of sampling, stages in the selection of a sample, types of sampling in quantitative researches, types of sampling in qualitative researches, and ethical Considerations in Data Collection.
This PPT tells you how to tackle with questions based on Data Interpretation in CAT 2009. Ample of PPTs of this type on every topic of CAT 2009 are available on www.tcyonline.com
Qualitative data analysis is often a tough job and many researchers find it difficult to get comprehensive presentation on the topic. This seminar is an attempt to fulfil that purpose.
Dedicated to the traditional Art of Bookmaking, as well as bookbinding and Handmade Book Design techniques from Doro Collection. Contact details provided.
Ideas for teaching chance, data and interpretation of dataJoanne Villis
These activities have been designed specifically for Year 3 students according to the Australian Curriculum guidelines. However, they can be adapted to meet other standards or year levels.
Biostatistics - the application of statistical methods in the life sciences including medicine, pharmacy, and agriculture.
An understanding is needed in practice issues requiring sound decisions.
Statistics is a decision science.
Biostatistics therefore deals with data.
Biostatistics is the science of obtaining, analyzing and interpreting data in order to understand and improve human health.
Applications of Biostatistics
Design and analysis of clinical trials
Quality control of pharmaceuticals
Pharmacy practice research
Public health, including epidemiology
Genomics and population genetics
Ecology
Biological sequence analysis
Bioinformatics etc.
This document is highly important for the learners of research methodology. A number of statistical terminologies are defined with examples for the simplicity of learners.
What are parametric and nonparametric inferential testsSolution.pdfarpaqindia
What are parametric and nonparametric inferential tests?
Solution
Inferential statistics suggest statements about a population based on a sample from that
population. Parametric inferential tests are carried out on data that follow certain parameters: the
data will be normal (i.e. the distribution parallels the bell curve); numbers can be added,
subtracted, multiplied and divided; variances are equal when comparing two or more groups; and
the sample should be large and randomly selected.
There are generally more statistical technique options for the analysis of parametric than non-
parametric data, and parametric statistics are considered to be the more powerful. Common
examples of parametric tests are: correlated t-tests and the Pearson r correlation coefficient.
Inferential statistics suggest statements or make predictions about a population based on a
sample from that population. Non-parametric tests relate to data that are flexible and do not
follow a normal distribution.
They are also known as.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
The Indian economy is classified into different sectors to simplify the analysis and understanding of economic activities. For Class 10, it's essential to grasp the sectors of the Indian economy, understand their characteristics, and recognize their importance. This guide will provide detailed notes on the Sectors of the Indian Economy Class 10, using specific long-tail keywords to enhance comprehension.
For more information, visit-www.vavaclasses.com
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
We all have good and bad thoughts from time to time and situation to situation. We are bombarded daily with spiraling thoughts(both negative and positive) creating all-consuming feel , making us difficult to manage with associated suffering. Good thoughts are like our Mob Signal (Positive thought) amidst noise(negative thought) in the atmosphere. Negative thoughts like noise outweigh positive thoughts. These thoughts often create unwanted confusion, trouble, stress and frustration in our mind as well as chaos in our physical world. Negative thoughts are also known as “distorted thinking”.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptx
Analysis and interpretation of data
1.
2. ANALYSIS and INTERPRETATION provide answers
to the research questions postulated in the study.
ANALYSIS means the ordering, manipulating, and
summarizing of data to obtain answers to research questions.
Its purpose is to reduce data to intelligible and interpretable
form so that the relations of research problems can be studied
and tested.
INTERPRETATION gives the results of analysis, makes
inferences pertinent to the research relations studied, and draws
conclusions about these relations.
3. STATISTICS is simply a tool in research. In fact, according to
Leedy (1974:21), statistics is a language which, through its own
special symbols and grammar, takes the numerical facts of life and
translates them meaningfully.
Statistics thus gathers numerical data. The variations of the data
gathered are abstracted based on group characteristics and
combined to serve the purpose of description, analysis,
interpretation, and possible generalization. According to
McGuigan (1987), in research, this is known as the process of
concatenation where the statements are “chained together” with
other statements.
4. There are two kinds of statistics:
DESCRIPTIVE STATISTICS – allows the
researcher to describe the population or sample used in
the study.
INFERENTIAL STATISTICS – draws inferences
from sample data and actually deals with answering the
research questions postulated which are, in some cases,
cause and effect relationship.
5. DESCRIPTIVE STATISTICS
describes the characteristics of the population or the sample. To
make them meaningful, they are grouped according to the
following measures:
Measures of Central Tendency or Averages
Measures of Dispersion or Variability
Measures of Noncentral Location
Measures of Symmetry and/or Asymmetry
Measures of Peakedness or Flatness
6. Measures of Central Tendency or Averages.
These include the mean, mode and the median. The mean
is a measure obtained by adding all the values in a
population or sample and dividing by the number of
values that are added (Daniel, 1991:19-20). The mode is
simply the most frequent score of scores (Blalock,
1972:72). The median is the value above and below
which one half of the observations fall (Norusis, (1984:B-
63)
7. Measures of Dispersion or Variability.
These include the variance, standard
deviation, and the range. According to
Daniel (1991:24), a measure of dispersion
conveys information regarding the amount
of variability present in a set of idea.
8. The VARIANCE is a measure of the dispersion of the set of scores.
It tells us how much the scores are spread out. Thus, the variance is a
measure of the spread of the scores; it describes the extent to which
the scores differ from each other about their mean.
STANDARD DEVIATION thus refers to the deviation of scores
from the mean. Where ordinal measures of 1-5 scales (low-high)
are used, data most likely have standard deviations of less than
one unless, the responses are extremes (i.e., all ones and all
fives).
The RANGE is defined as the difference between the highest and
lowest scores (Blalock, 1972:77)
9. Measures of Noncentral Location. These include
the quantiles (i.e., percentiles, deciles, quartiles). The word
percent means “per hundred”. Therefore, in using
percentages, size is standardized by calculating the number of
individuals who would be in a given category if the total
number of cases were 100 and if the proportion in each
category remains unchanged. Since proportions must add to
unity, it is obvious that percentages will sum up to 100 unless
the categories are not mutually exclusive or exhaustive
(Blalock, 1972:33)
10. Measures of Symmetry and/or Asymmetry.
These include the skewness of the frequency distribution. If a
distribution is asymmetrical and the larger frequencies tend to
be concentrated toward the low end of the variable and the
smaller frequencies toward the high end, it is said to be
positively skewed. If the opposite holds, the larger frequencies
being concentrated toward the high end of the variable and the
smaller frequencies toward the low end, the distribution is
said to be negatively skewed (Ferguson and Takane, 1989:30).
11. Measures of Peakedness or Flatness of one
distribution in relation to another is referred to as Kurtosis. If
one distribution is more peaked than another, it may be
spoken of as more leptokurtic. If it is less peaked, it is said to
be more platykurtic.
12. NONPARAMETRIC TESTS
Two types of data are recognized in the application of statistical
treatments, these are: parametric data and nonparametric data.
Parametric data are measured data and parametric statistical tests
assume that the data are normally, or nearly normally, distributed
(Best and Kahn, 1998:338).
Nonparametric data are distribution free samples which implies
that they are free, of independent of the population distribution
(Ferguson and Takane, 1989:431).
The tests on these data do not rest on the more stringent assumption
of normally distributed population (Best and Kahn, 1998:338).
13. Kolmogorov – Smirnov test - fulfills the function of
chi-square in testing goodness of fit and of the Wilcoxon
rank sum test in determining whether random samples are
from the same population.
Sign Test - is important in determining the significance
of differences between two correlated samples. The
“signs” of the test are the algebraic plus or minus values
of the difference of the paired scores.
Median Test - is a sign test for two independent
samples in contradistinction to two correlated samples, as
is the case with the sign test.
14. Spearman rank order correlation - sometimes called
Spearman rho (p) or Spearman’s rank difference correlation, is a
nonparametric statistic that has its counterpart in parametric
calculations in the Pearson product moment correlation.
Kruskal – Wallis – sometimes known as the Kruskal-Wallis H
test of ranks for k independent samples. The H is the title of the test
and stands for the null hypothesis; and the k for the classes or
samples.
Kendall coefficient of concordance – is also known as
Kendall’s coefficient W or the concordance coefficient of W. it is a
technique which can be used with advantage in studies involving
rankings made by independent judges.
15. The nonparametic tests available are:
Mann-Whitney U-test - in nonparametric statistics is the
counterpart of the t-test in parametric measurements. It may find
use in determining whether the medians of two independent
samples differ from each other to a significant degree.
Wilcoxon match pairs, signed rank test – is employed
to determine whether two samples differ from each other to a
significant degree when there is a relationship between the
samples.
Wilcoxon rank sum test – may be used in those
nonparametric situations where measures are expressed as
ranked data in order to test the hypothesis that the samples are
from a common population whose distribution of the measures is
the same as that of the samples.
16. APPROPRIATE STATISTICAL METHODS BASED ON THE
RESEARCH PROBLEM AND LEVELS OF MEASUREMENT
the statistical methods appropriate to any studies are always
determined by the research problem and the measurement scale of
the variables used in the study.
CHI - SQUARE
the most commonly used nonparametric test. It is employed in
instances where a comparison between observed and theoretical
frequencies is present, or in testing the mathematical fit of a
frequency curve to an observed frequency distribution.
17. T - TESTS
provides the capability of computing student’s t and probability
levels for testing whether or not the difference between two samples
means is significant (Nie, et al., 1975:267). This type of analysis is
the comparison of two groups of subjects, with the group means as
the basis for comparison.
Two types of T-tests may be performed:
Independent Samples - cases are classified into 2 groups and a test
of mean differences is performed for specified variables;
Paired Samples – for paired observations arrange casewise, a test
of treatment effects is performed.
18. CORRELATION ANALYSIS
Correlation is used when one is interested to know the relationship
between two or more paired variables. According to Blalock
(1972:361), this is where interest is focused primarily on the
exploratory task of finding out which variables are related to a given
variable.