Stats 1

EDUCATIONAL STATISTICS
A. QUESTIONS:
1. what is the role of descriptive and inferential statistics as part of quantitative
research?
Inferential statistics and descriptive statistics are two major subfields of statistics. I
demonstrate how both kinds of statistics are crucial for various purposes in this blog
article. It's interesting that while the objectives and approaches differ greatly, certain
statistical measurements are comparable. Put the data for a selected group into a
summary and a graph using descriptive statistics. You can comprehend that precise
collection of observations through this procedure. Data from a sample is used in
inferential statistics to form conclusions about the wider population from which the
sample was collected. We need to be certain that our sample properly represents the
population since the purpose of inferential statistics is to derive findings from a
sample and generalize them to a population.
2. How do you demonstrate the usefulness of descriptive and inferential statistics as

part of
quantitative research methodology?
Statistical techniques can be categorized as Descriptive Statistics and Inferential
Statistics. We use descriptive statistics to describe a situation, while we use
inferential statistics to explain the probability of occurrence of an event. We use
charts, graphs, and tables to represent descriptive statistics, while we use probability
methods for inferential statistics. It is simpler to perform a study using descriptive
statistics rather than inferential statistics, where you need to establish a relationship
between variables in an entire population.
3. How do you compare statistical procedures for different purposes?

Selection of appropriate statistical method is very important step in analysis of
biomedical data. A wrong selection of the statistical method not only creates some
serious problem during the interpretation of the findings but also affects the
conclusion of the study. In statistics, for each specific situation, statistical methods
are available to analysis and interpretation of the data. To select the appropriate
statistical method, one need to know the assumption and conditions of the statistical
methods, so that proper statistical method can be selected for data analysis.ther
than knowledge of the statistical methods, another very important aspect is nature
and type of the data collected and objective of the study because as per objective,
corresponding statistical methods are selected which are suitable on given data.
4. How do you describe quantitative results using descriptive statistics.
Descriptive statistics are used to describe the basic features of the data in a study.
They provide simple summaries about the sample and the measures. Together with
simple graphics analysis, they form the basis of virtually every quantitative analysis
of data. Descriptive Statistics are used to present quantitative descriptions in a
manageable form. In a research study we may have lots of measures. Or we may
measure a large number of people on any measure. Descriptive statistics help us to
simplify large amounts of data in a sensible way. Each descriptive statistic reduces
lots of data into a simpler summary.
5. why do you think that statistics is useful to all types of research, especially thesis,
dissertation, etc?
The field of statistics is the science of learning from data. Statistical knowledge helps
you use the proper methods to collect the data, employ the correct analyses, and
effectively present the results. Statistics is a crucial process behind how we make
discoveries in science, make decisions based on data, and make predictions.
Statistics allows you to understand a subject much more deeply.
B. TERMS:
Directions: Look for the meaning and give an example of each of the following terms:
1. Population means
The population mean is an average of a group characteristic. The group could be a
person, item, or thing, like “all the people living in the United States” or “all dog
owners in Georgia”. In statistics, it’s actually rare that you can calculate the
population mean. That’s because asking an entire population about something is
usually cost prohibitive or too time consuming.
2. Subpopulation or sample means

A sample is a condensed collection of information that a researcher selects or picks
from a broader population using a predetermined technique of selection. These
components are referred to as observations, sampling units, or sample points.
Developing a sample is a productive way to carry out research. The entire population
must frequently be studied, which is difficult, expensive, and time consuming.
3. Median
The median is the value in the center of a group of numbers. The median
corresponds to the 50th percentile of the collection of numbers. In other terms, the
median is the value in the center of a group of numbers where half of the values are
less than the median and half are more than the median.
4. Mode
The most common value in a data collection is called the mode or modal value. It is
a measure of central tendency that reveals the most prevalent option or feature in
your sample.
5. Mean
The mean (aka the arithmetic mean, different from the geometric mean) of a dataset
is the sum of all values divided by the total number of values. It's the most commonly
used measure of central tendency and is often referred to as the “average.”
6. Variance
Variance is a measure of variation. It is determined by averaging the squared
deviations from the mean. The degree of dispersion in your data collection is
indicated by variation. The greater the spread of the data, the greater the variance in
proportion to the mean.
7. Frequency
The number of times a specific value appears in the data is its frequency (f). A
variable's distribution is its frequency pattern, or the collection of all conceivable
values and the frequencies corresponding to those values. Frequency tables or
charts are used to represent frequency distributions.
8. Hypothesis
One of the words that people misuse while assuming they know what it means is
"hypothesis." Within academic research, it has a very specific connotation, though.
So, it's crucial to comprehend the specific meaning before formulating a theory.
9. Linear Regression
A variable's value can be predicted using linear regression analysis based on the
value of another variable. The dependent variable is the one you want to be able to
forecast. The independent variable is the one you're using to make a prediction
about the value of the other variable.
10. Probability
Probability sampling is the choosing of a sample from a population based on the idea
of randomization, often known as random selection or chance. Probability sampling
is more difficult, time-consuming, and typically more expensive than non-probability
sampling.

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EDUCATIONAL STATISTICS

2. How do you demonstrate the usefulness of descriptive and inferential statistics as

3. How do you compare statistical procedures for different purposes?

2. Subpopulation or sample means

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