CHAPTER 4 Flashcards
This mode of presentation combines text and
figures in a statistical report
- TEXTUAL PRESENTATION
This mode of presentation is better than the textual form
because the data are presented in more concise and systematic
manner. The data are systematically presented through tables
consisting of vertical columns and horizontal rows with headings
describing these rows and columns
- TABULAR PRESENTATION
It is a most effective means of presenting statistical data,
because important relationships are brought out more clearly
in graphs.
❑ Graphs have a great advantage over tables because graphs
convey quantitative value and compares more readily than
tables. Besides, readers are more likely to read graphs than
tables.
- GRAPHIC PRESENTATION
s the simplest form of graphic presentation. It is generally intended for
comparison of simple magnitude. It may either be horizontal bar graph or a vertical bar
graph.
- Bar Graph
It is the most widely used practical device effective in showing a trend (changes in value) over
a period.
- Line Graph
divided into parts whose sizes are proportional to the magnitude or percentages
they represent. It is used to show the component parts of a whole. In making a pie-chart the
following rules may be followed in order not to mislead the readers.
- Circle Graph/ Pie Graph
provides a means for visual inspection of
data which a list of values for two variables cannot. It shows if a
relationship exists between variables. It also convey both
direction and shape of the relationship
- Scatter Diagram
uses pictorial symbols such as a stick figure
for population to indicate data instead of a bar in a bar-type chart
- Pictograph/ Pictogram
The lowest level, involves using numbers simply to
categorize attributes. Examples of variables that
are nominally measured include gender and blood
type.
▪ Nominal measurement provides information only
about categorical equivalence and nonequivalence and so the numbers cannot be
treated mathematically.
Nominal measurement.
It ranks objects based on their relative standing on
an attribute. If a researcher orders people from
heaviest to lightest, this is ordinal measurement
. Ordinal measurement
It occurs when researchers can specify
the ranking of objects on an attribute and
the distance between those objects. Most
educational and psychological tests yield
interval-level measures.
Interval measurement.
This is the highest level. Ratio scales, unlike interval scales,
have a rational, meaningful zero and therefore provide
information about the absolute magnitude of the attribute.
- Ratio measurement.
which is concerned with the collection,
classification and presentation of data designed to summarize and describe the
group characteristics of the data. Examples are the measures of central
tendency or location and measures of variability
DESCRIPTIVE STATISTICS
– refers to the drawing of conclusions or judgment
about a population based on a representative sample systematically taken from
the same population. Its aim is to give concise information about large groups
of data without dealing with each and every element of these groups.
INFERENTIAL STATISTICS
STEPS IN A STATISTICAL INQUIRY OR INVESTIGATION
- Collection of data
- Processing of data
- Presentation of data
- Analysis of data
- Interpretation of data
MEASURES OF CENTRAL TENDENCY
MEAN
✓ MEDIAN
✓ MODE
a) higher statistical computations.
b) distribution where there are no extreme values since it is easily affected by
extremely high or low values.
c) distribution requiring the greatest reliability since it includes all the given values
in its computation.
d) interval and ratio measurements.
❖ The mean is equal to the sum of all values divided by the number of participants—
what people refer to as the average
MEAN
a) ordinal and ranked measurements.
b) distributions which are markedly skewed.
c) distributions where the highest or lowest class interval or both are not defined,
that is, distributions using open-ended classes such as 100 and below or 60 and above.
d) determination of whether the cases fall within the lower halve or the upper
halve of a distribution (appropriate locator of central tendency.is the point in a distribution that divides scores in half. The middle
number; found by ordering all data points and picking out the one in the middle (or if
there are two middle numbers, taking the mean of those two numbers) Consider the
following set of values:
MEDIAN
e is used for:
a) nominal data
b) Solving for the most typical average since it is the value that occur most
frequently in a series.
c) a quick or rough estimate of a central value.
❖ The mode is the number that occurs most frequently in a distribution. In the
following distribution, the mode is 53:
MODE
CORRELATION ANALYSIS
THE PEARSON PRODUCT-MOMENT CORRELATION COEFFICIENT
CHI-SQUARE
❖ T-TEST FOR INDEPENDENT SAMPLES
❖ T-TEST FOR DEPENDENT SAMPLES
❖ ANALYSIS OF VARIANCE (ANOVA)
❖ LINEAR REGRESSION
INFERENTIAL STATISTICS
used to measure the nature of relationship or association between variables.
❑ The most meaningful research is that which seeks to find and to verify relationships
between and among variables.
❑ In correlational studies, researchers determine if a relationship exists between two
(or more) quantitative variables, such as score and age or reading comprehension
and word-problem solving skill in mathematics.
❑ Such relationships are oftentimes used in prediction, to imply causation. Although
causal relationship cannot be proven through correlational researchers, researchers
hope eventually to make causal statements as an outgrowth of their work.
❑ “SIGNIFICANT RELATIONSHIP”
CORRELATION ANALYSIS
The degree of association or closeness of relationship between two variables
is measured by a correlation coefficient, denoted by r
THE PEARSON PRODUCT-MOMENT CORRELATION COEFFICIENT
For tables with two rows and two columns, select Chi-square to calculate the Pearson chisquare, the likelihood-ratio chi-square, Fisher’s exact test, and Yates’ corrected chi-square
(continuity correction).
❑ When both table variables are quantitative, Chi-square yields the linear-by-linear
association test.
CHI-SQUARE
When sample size is small, n<30 we use the T-test
❑“SIGNIFICANT DIFFERENCEUsed when we want to compare 2 GROUPS of INDEPENDENT VARIABLES
T-TEST
is applied to matched pairs of correlated
samples. The samples are supposedly taken from one population.
❑ “SAME GROUP”
T-TEST FOR DEPENDENT SAMPLES/ PAIRED SAMPLE T-TEST
❑ “Fill Up Test Value”
ONE SAMPLE T-TEST
To test the equality of several means, researchers utilize a procedure known as the analysis of variance. One-factor
analysis of variance is a procedure that uses a set of calculations on several variances to test the hypothesis that
several populations have the same mean. The application of ANOVA requires three basic assumptions.
❑ F test
❑ 3 or more variables
ANOVA (ANALYSIS OF VARIANCE)
is the term used to describe the process of estimating the
relationship between two variables. The relationship is estimated by fitting a
straight line through the given data.
❑ “Cause and Effect”
❑ Determine the Independent and Dependent Variable
LINEAR REGRESSION
Tracking the
occurrence, position and meaning of words or
phrases
Qualitative content analysis
Closely examining the data to
identify the main themes and patterns
Thematic analysis:
Studying how communication
works in social context
Discourse analysis:
Steps in Analyzing Qualitative Researchv
search for patterns
and themes
validation of the
thematic analysis.
weave the
thematic strands together into an integrated picture
