STATISTICS-FOR-MA-CLASS-MARK-RUSTOM-C.-VALENTIN.pdf

Sep 12, 20220 likes3 views

This document discusses statistical concepts and their practical applications. It defines key terms like descriptive statistics, inferential statistics, measures of central tendency, and levels of measurement. It also explains how to differentiate between descriptive and inferential statistics, when to use various statistical tools, and how to interpret statistical outputs. Examples of how to apply these statistical analysis concepts in work contexts are provided.

With Practical Applications
MARK RUSTOM C. VALENTIN
Discussant
markrustom.valentin@deped.gov.ph

• Types of Data
• Descriptive Statistics
• Inferential Statistics
• Statistical Data Analysis Application

• To have knowledge or idea in statistical tests/tools.
• To know when to use each of the statistical tools.
• To know how to differentiate descriptive and
inferential statistics
• To know how to interpret the statistical output.
• To solve for the appropriate number of samples.
• To apply the statistical analysis tools in your
respective field of work.

• Is derived from the Latin word “STATUS”,
meaning “state”.
• Is the science of collecting, classifying,
organizing, summarizing, analyzing, and
interpreting data in order to draw
conclusions or make decisions

STATISTICS-FOR-MA-CLASS-MARK-RUSTOM-C.-VALENTIN.pdf

• Deals with the collection and presentation
of data and collection of summarizing
values to describe its group characteristics

MEAN
• The arithmetic average of a distribution
MEDIAN
• The middle value that separates the higher
values and the lower values equally
MODE
• The most frequently occurring value

STANDARD DEVIATION
• A measure of dispersion around the mean
VARIANCE
• The square of the standard deviation
MINIMUM
• The lowest value
MAXIMUM
• The highest value
RANGE
• The difference between maximum and minimum

- Measures the symmetry of a distribution
• Symmetric – not skewed (mean=median=mode)
• Positively Skewed – skewed to the right; long
right tail (mean>median>mode)
• Negatively Skewed – skewed to the left; long left
tail (mean<median<mode)

Two distributions have the same skewness value of 1.0
The standard error for the first distribution is 0.49; while the second
has 0.51.
Which distribution may be considered symmetric?
Which distribution may be considered skewed?
RULE:
• If skewness > 2 * standard error, then skewed.
• If skewness ≤ 2 * standard error, then symmetric.

- Measures the extent to which observations cluster
around a central point
• Mesokurtic – normal distribution
• Platykurtic – cluster less than a normal
distribution; flatter peak around the mean and fat
tails
• Leptokurtic – cluster more than a normal
distribution; higher peak around the mean and
thin tails

RULE:
• |kurtosis| ≤ 2 * standard error, then mesokurtic
• |kurtosis| > 2 * standard error, then:
platykurtic if kurtosis is negative (-)
leptokurtic if kurtosis is positive (+)

• Deals with predictions and inferences
based on the analysis and interpretation of
the results of the information gathered by
the statistician.

Generalize from samples to population
Test relationships
Test differences
Make predictions

NOMINAL DATA
• Numbers in the variable are used only to classify
the data. In this level of measurement, words,
letters, and alpha-numeric symbols can be used.
Examples:
Gender
Marital Status
Measure of Central Tendency: Mode

ORDINAL DATA
• Has all the characteristics of the nominal level
and it has ordering information.
Examples:
Tenure
Position
Likert Scales
Measure of Central Tendency: Median and Mode

3-point interval 4-point interval 5-point interval
2.33 – 3.00
1.67 – 2.32
1.00 – 1.66
3.25 – 4.00
2.50 – 3.24
1.75 – 2.49
1.00 – 1.74
4.20 – 5.00
3.40 – 4.19
2.60 – 3.39
1..80 – 2.59
1.00 – 1.79

INTERVAL DATA
• It does not only classify and order the measurements,
but it also specifies the distances between each
interval on the scale are equivalent along the scale
from low interval to high interval.
Examples:
Average Handle Time (AHT)
Temperature
IQ Score
Measure of Central Tendency: 3Ms

RATIO DATA
• It has all the characteristics of an interval level
and it can have absolute zero value.
Examples:
Grades
Scores in Test
NAT
Absenteeism
Measure of Central Tendency: 3Ms

Cronbach’s Alpha is a measure of internal consistency, that is, how
closely related a set of items are as a group.

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STATISTICS-FOR-MA-CLASS-MARK-RUSTOM-C.-VALENTIN.pdf

1. With Practical Applications MARK RUSTOM C. VALENTIN Discussant markrustom.valentin@deped.gov.ph

2. • Types of Data • Descriptive Statistics • Inferential Statistics • Statistical Data Analysis Application

3. • To have knowledge or idea in statistical tests/tools. • To know when to use each of the statistical tools. • To know how to differentiate descriptive and inferential statistics • To know how to interpret the statistical output. • To solve for the appropriate number of samples. • To apply the statistical analysis tools in your respective field of work.

4. • Is derived from the Latin word “STATUS”, meaning “state”. • Is the science of collecting, classifying, organizing, summarizing, analyzing, and interpreting data in order to draw conclusions or make decisions

8. • Deals with the collection and presentation of data and collection of summarizing values to describe its group characteristics

12. MEAN • The arithmetic average of a distribution MEDIAN • The middle value that separates the higher values and the lower values equally MODE • The most frequently occurring value

26. STANDARD DEVIATION • A measure of dispersion around the mean VARIANCE • The square of the standard deviation MINIMUM • The lowest value MAXIMUM • The highest value RANGE • The difference between maximum and minimum

36. - Measures the symmetry of a distribution • Symmetric – not skewed (mean=median=mode) • Positively Skewed – skewed to the right; long right tail (mean>median>mode) • Negatively Skewed – skewed to the left; long left tail (mean<median<mode)

37. Two distributions have the same skewness value of 1.0 The standard error for the first distribution is 0.49; while the second has 0.51. Which distribution may be considered symmetric? Which distribution may be considered skewed? RULE: • If skewness > 2 * standard error, then skewed. • If skewness ≤ 2 * standard error, then symmetric.

39. - Measures the extent to which observations cluster around a central point • Mesokurtic – normal distribution • Platykurtic – cluster less than a normal distribution; flatter peak around the mean and fat tails • Leptokurtic – cluster more than a normal distribution; higher peak around the mean and thin tails

40. RULE: • |kurtosis| ≤ 2 * standard error, then mesokurtic • |kurtosis| > 2 * standard error, then: platykurtic if kurtosis is negative (-) leptokurtic if kurtosis is positive (+)

42. • Deals with predictions and inferences based on the analysis and interpretation of the results of the information gathered by the statistician.

44. Generalize from samples to population Test relationships Test differences Make predictions

46. NOMINAL DATA • Numbers in the variable are used only to classify the data. In this level of measurement, words, letters, and alpha-numeric symbols can be used. Examples: Gender Marital Status Measure of Central Tendency: Mode

47. ORDINAL DATA • Has all the characteristics of the nominal level and it has ordering information. Examples: Tenure Position Likert Scales Measure of Central Tendency: Median and Mode

48. 3-point interval 4-point interval 5-point interval 2.33 – 3.00 1.67 – 2.32 1.00 – 1.66 3.25 – 4.00 2.50 – 3.24 1.75 – 2.49 1.00 – 1.74 4.20 – 5.00 3.40 – 4.19 2.60 – 3.39 1..80 – 2.59 1.00 – 1.79

49. INTERVAL DATA • It does not only classify and order the measurements, but it also specifies the distances between each interval on the scale are equivalent along the scale from low interval to high interval. Examples: Average Handle Time (AHT) Temperature IQ Score Measure of Central Tendency: 3Ms

50. RATIO DATA • It has all the characteristics of an interval level and it can have absolute zero value. Examples: Grades Scores in Test NAT Absenteeism Measure of Central Tendency: 3Ms

94. Cronbach’s Alpha is a measure of internal consistency, that is, how closely related a set of items are as a group.

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