Research Problem:
Over the years there has been an increasingly high demand for speech language pathology services. Although this increase is embraced by the profession, the added caseload has created pressure to keep up with expectations placed upon the speech-language pathologists (SLP).According to ASHA’s 2016 Schools Survey, there is current evidence that caseload affects many factors within the roles of an SLP in the school setting, creating a difference in case management within this setting. Caseload requires the effective use of qualitative and quantitative elements of the services they provide (Kenny and Lincoln, 2012).Continuation in attached file….
Research Applications
SLHS 491
Analyzing Quantitative Data
Exploring and Organizing a Data Set
• Statistics: computational procedures that enable us to
find patterns and meaning in numerical data
• Data need to be organized before they are analyzed
• Whatever the researcher does to prepare will affect the
meaning that the data reveal
• Every researcher should be able to provide a clear,
logical rationale for the procedure used data
Organizing Data
• To identify patterns, first organize the data in meaningful
ways
– In a table
– In a graph
Use the Computer to Organize and Analyze
Data
• Electronic spreadsheet: a software program that allows a
researcher to manipulate data displayed in a table
• Uses of electronic spreadsheets:
– Sorting data
– Recoding data
– Calculating formulas
– Graphing from the data
– Employing “trial and error” explorations
Choosing Statistics
• Two major functions of statistics
– Descriptive statistics describe what the data look
like, how broadly they are spread, and how closely
two or more variables within the data are associated
with another.
– Inferential statistics allow us to draw inferences
about large populations by collecting data on
relatively small samples.
Statistics as Estimates of Population
Parameters
• Parameter:
– characteristic or quality of a population
▪ Parameters of a circle
– diameter is twice the radius (r)
– circumference is always
– area is always
– Statistic
▪Any calculation we perform for the sample rather
than the population
The Nature of the Data (1 of 5)
• The nature of the data helps determine the statistic that is
necessary
– Have your data been collected for a single group or
for two or more groups
– Were continuous or discrete variables involved
▪ Continuous = infinite number of possible values
▪ Discrete = finite, small number of possible values
that are independent of each other
The Nature of the Data (2 of 5)
• The nature of the data helps determine the statistic that is
necessary
– Do you have nominal, ordinal, interval, or ratio data
▪ Nominal = separate, non-ranked categories
▪ Ordinal = sequenced categories
▪ Interval = sequenced categories with equal units of
measurement
▪ Ratio = equal intervals AND true zero point
The Nature of the Data (3 of 5)
• Many statistical procedures are built on the notion of a
normal distribution. You may know this as the “bell curve”
or the “normal curve.” This normal distribution has
several distinguishing characteristics:
1. It is horizontally symmetrical.
2. Its highest point is at its midpoint.
3. Predictable percentages of the population like within
any given portion of the curve.
The Nature of the Data (4 of 5)
• The nature of the data helps determine the statistic that is
necessary
– Are the data normally distributed, skewed, or kurtic?
▪ Normal: Horizontally symmetrical frequency
distribution – scores at the center are most
frequent
▪ Predictable percentages of the population lie within
any given portion of the normal curve
The Nature of the Data (5 of 5)
• The nature of the data helps determine the statistic that is
necessary
– Skewed: Not symmetrical – scores that are most
frequent can be anywhere along the X axis
▪ Peak to the left of midpoint = positively skewed
▪ Peak to the right of the midpoint = negatively
skewed
– Kurtic: peaked/pointy (leptokurtic) or flat (platykurtic)
▪ Percentile ranks are an example
Choosing between Parametric and
Nonparametric Statistics
• Parametric statistics are used when
– data reflect an interval or ratio scale
– data fall in a normal distribution
• Nonparametric statistics are used when
– data are ordinal in nature
– data distribution is non-normal
Descriptive Statistics
• Measures of central tendency
• Measures of variability
• Measures of association
Measures of Central Tendency (1 of 2)
• Techniques for finding a central point around which the
data revolve
• Descriptive statistics describe a body of data.
• Three things a researcher might want to know about the
data set:
1. Points of central tendency
2. Amount of variability
3. Extent to which two or more variables are associated with one another
Measures of Central Tendency (2 of 2)
• Mode: the single number or score that occurs most
frequently
• Median: the numerical center of a set of data – the
number in the middle of the (ordered) set of scores
• Mean: the arithmetic average of the scores within the
data set
– May need geometric mean for some data sets (e.g.,
growth)
Measures of Variability (1 of 3)
• Extent to which data points cluster around point of central
tendency
– Range: value reflecting the spread of data from
lowest to highest value (highest score minus lowest
score)
– Interquartile range: Quartile 3 – Quartile 1
– Five-number summary (lowest, highest, Q1, Q3, and
median)
Measures of Variability (2 of 3)
• Average deviation: the average of differences of each
score and the mean score
• Standard deviation: standardized way of computing the
distance between each score and the mean; takes
negative numbers into account
– the measure of variability most commonly used in
statistical procedures
Measures of Variability (3 of 3)
• Norm-referenced score: reflects where each person in
the group is, relative to other members of the group
• Standard score: tells us how far an individual’s
performance is from the mean, with respect to standard
deviation units
Keep It in Perspective
• Statistics related to central tendency and variability
provide a beginning point from which to view data
• Statistical manipulation of the data is not research
• Research demands interpretation of the data
Measures of Association
• Correlation: statistical process that allows the researcher
to identify any relationship between variables
– Results in a statistic (number) between −1 and +1
– This number is known as a correlation coefficient
Correlation (1 of 2)
• Correlation tells us direction
– Positive: as one variable increases, the other variable also
increases
– Negative: as one variable increases, the other variable
decreases
• Closer to +1 or −1: strong correlation
– Variables closely related
– Can make predictions
• Closer to 0: weak correlation
Correlation (2 of 2)
• A variety of statistical tests measure correlation
• Correlation does not necessarily imply causation
– Ask yourself, “What might be the underlying reason
for the association?”
Inferential Statistics
• Used to draw inferences about a population from a
smaller sample
• Two main functions:
1. Estimate population parameter from a random sample
2. Test statistically based hypotheses
Estimating Population Parameters (1 of 2)
• Point estimate: single statistic that is taken as a
reasonable estimate of the corresponding population
parameter
– Example: Sample mean used to estimate population
mean
– Typically does not correspond exactly with its true
equivalent in the population
Estimating Population Parameters (2 of 2)
• Interval estimate: a range within which a population
parameter probably lies
• Sometimes called “confidence interval”
– Attaches a certain level of confidence that the
estimated range does indeed contain the population
parameter
Testing Hypotheses (1 of 2)
• Researchers begin with a null hypothesis
– Any result observed is the result of chance alone
Testing Hypotheses (2 of 2)
• Testing the Null Hypothesis
– Using data from a sample to make inferences about the
population from which the sample is drawn
– Are these results simply “due to chance” – the fact that this
specific sample was tested
– Do the results accurately reflect the population
• Researchers reject “chance alone” if the results surpass a preset cutoff level
• “Significance Level” or “alpha level” (a)
Errors in Hypothesis Testing (1 of 2)
• Type I error
– Incorrectly rejecting the null hypothesis
– “This result is not due to chance” – but it really IS due
to chance
Errors in Hypothesis Testing (2 of 2)
• Type II Error
– Concluding that a result was due to chance when in
fact it was not
– Failing to reject a null hypothesis that is actually false
– Also known as a beta error
Suggestions for Increasing the Power of a
Statistical Test
• Use as large a sample as is reasonably possible
• Maximize the validity and reliability of your measures
• If logically defensible and logistically practical, obtain
repeated measures of your dependent variable
• Use parametric rather than non-parametric statistics
whenever possible
Meta-Analysis
• Used to analyze and draw conclusions about other
researchers’ statistical analyses
• When conducting a meta-analysis, the researcher:
– Conducts an extensive search for relevant studies
– Identifies appropriate studies to include in the metaanalysis
– Converts each study’s results to a common statistical
index
Statistical Software Packages
• Commercially available options include:
– SPSS, SAS, SYSTAT, Minitab, Statistica
• Freeware programs include AdaMSoft and R, for
example
• Advantages of using a statistical program
–
–
–
–
Range of available statistics
User-friendliness
Assumption testing
Graphics
Interpretation of the Data
• Interpreting the data means several things:
1. Relating the findings to the original research problem
and to the specific research questions and
hypotheses
2. Relating the findings to preexisting literature,
concepts, theories, and research studies
3. Determining whether the findings have practical
significance as well as statistical significance
4. Identifying limitations of the study
Copyright
Current caseload size
41-45
66+
56-60
66+
0-25
0-25
36-40
41-45
51-55
51-55
51-55
46-50
36-40
36-40
51-55
0-25
61-65
56-60
61-65
66+
66+
41-45
56-60
66+
61-65
51-55
56-60
56-60
36-40
41-45
56-60
51-55
31-35
26-30
36-40
31-35
36-40
0-25
41-45
31-35
46-50
56-60
The size of my caseload affects the quality of my therapy.
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Neither agree nor disagree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Neither agree nor disagree
Strongly agree
Neither agree nor disagree
Strongly agree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Somewhat disagree
Strongly agree
Strongly agree
46-50
61-65
66+
51-55
66+
31-35
66+
31-35
66+
51-55
56-60
36-40
31-35
66+
41-45
0-25
46-50
46-50
36-40
61-65
46-50
66+
66+
56-60
36-40
51-55
61-65
56-60
66+
36-40
51-55
56-60
46-50
0-25
46-50
56-60
36-40
51-55
46-50
46-50
66+
66+
61-65
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
Strongly agree
Somewhat agree
Strongly agree
Somewhat agree
Neither agree nor disagree
Somewhat agree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
56-60
56-60
46-50
56-60
56-60
31-35
36-40
26-30
46-50
31-35
61-65
41-45
46-50
51-55
26-30
56-60
66+
66+
26-30
36-40
0-25
26-30
51-55
51-55
31-35
41-45
46-50
51-55
61-65
36-40
66+
0-25
46-50
0-25
0-25
66+
0-25
66+
26-30
26-30
31-35
46-50
61-65
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
Strongly agree
Somewhat agree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly disagree
Strongly agree
Strongly agree
Strongly agree
Neither agree nor disagree
Strongly agree
Somewhat agree
Somewhat agree
Strongly agree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
66+
56-60
36-40
41-45
41-45
61-65
51-55
31-35
46-50
41-45
61-65
66+
66+
56-60
46-50
26-30
41-45
66+
46-50
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Somewhat agree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
The quality of my therapy would increase if my caseload were to decrease.
Neither agree nor disagree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Somewhat disagree
Strongly agree
Strongly agree
Neither agree nor disagree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
Somewhat agree
Strongly agree
Somewhat agree
Somewhat agree
Neither agree nor disagree
Strongly agree
Strongly agree
Somewhat agree
Somewhat agree
Strongly agree
Neither agree nor disagree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Neither agree nor disagree
Strongly agree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
Strongly agree
Somewhat agree
Strongly agree
Somewhat agree
Neither agree nor disagree
Somewhat agree
Somewhat disagree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
Strongly disagree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
Strongly agree
Somewhat agree
Somewhat agree
Somewhat disagree
Strongly agree
Strongly agree
Strongly agree
Neither agree nor disagree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
Strongly agree
I am satisfied with my current position.
Somewhat agree
Somewhat disagree
Somewhat agree
Strongly disagree
Somewhat agree
Strongly agree
Somewhat agree
Neither agree nor disagree
Neither agree nor disagree
Somewhat agree
Somewhat agree
Somewhat agree
Strongly agree
Strongly agree
Somewhat disagree
Somewhat agree
Somewhat agree
Somewhat agree
Strongly agree
Strongly disagree
Somewhat disagree
Somewhat agree
Somewhat disagree
Strongly disagree
Somewhat agree
Somewhat agree
Somewhat disagree
Somewhat agree
Strongly agree
Strongly agree
Neither agree nor disagree
Somewhat agree
Somewhat agree
Strongly agree
Somewhat disagree
Somewhat agree
Somewhat agree
Strongly agree
Strongly disagree
Strongly agree
Somewhat agree
Somewhat agree
Complete work at work
Somewhat agree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly disagree
Somewhat disagree
Strongly disagree
Strongly disagree
Strongly disagree
Somewhat disagree
Strongly disagree
Strongly disagree
Somewhat disagree
Somewhat agree
Strongly disagree
Strongly disagree
Strongly disagree
Somewhat disagree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly disagree
Somewhat agree
Strongly disagree
Strongly agree
Somewhat disagree
Strongly agree
Strongly disagree
Strongly disagree
Strongly disagree
Somewhat agree
Somewhat disagree
Somewhat disagree
Somewhat disagree
Strongly disagree
Planning time/week
1-2
1-2
1-2
1-2
5-6
3-4
1-2
1-2
3-4
1-2
1-2
1-2
1-2
3-4
5-6
1-2
1-2
1-2
3-4
3-4
1-2
5-6
3-4
1-2
1-2
5-6
1-2
1-2
3-4
5-6
1-2
1-2
3-4
1-2
3-4
5-6
1-2
1-2
1-2
1-2
1-2
1-2
Somewhat disagree
Neither agree nor disagree
Somewhat disagree
Strongly agree
Somewhat disagree
Strongly disagree
Somewhat agree
Somewhat agree
Somewhat agree
Somewhat disagree
Neither agree nor disagree
Somewhat disagree
Strongly agree
Strongly disagree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Strongly agree
Somewhat agree
Somewhat agree
Somewhat agree
Strongly agree
Somewhat agree
Strongly agree
Strongly agree
Strongly disagree
Somewhat disagree
Somewhat agree
Strongly agree
Somewhat agree
Somewhat agree
Strongly agree
Strongly agree
Somewhat disagree
Strongly agree
Somewhat agree
Neither agree nor disagree
Somewhat disagree
Somewhat agree
Neither agree nor disagree
Somewhat agree
Strongly agree
Strongly disagree
Strongly disagree
Strongly disagree
Somewhat agree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly agree
Somewhat agree
Strongly disagree
Neither agree nor disagree
Somewhat agree
Strongly agree
Strongly disagree
Neither agree nor disagree
Strongly disagree
Strongly agree
Somewhat agree
Somewhat disagree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly agree
Neither agree nor disagree
Strongly agree
Strongly disagree
Somewhat disagree
Somewhat agree
Somewhat disagree
Neither agree nor disagree
Somewhat disagree
Strongly disagree
Somewhat agree
Somewhat disagree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly disagree
Somewhat disagree
Strongly disagree
Strongly disagree
Strongly disagree
Somewhat agree
1-2
1-2
1-2
1-2
3-4
5-6
1-2
1-2
1-2
1-2
1-2
1-2
7+
1-2
1-2
3-4
1-2
1-2
1-2
1-2
3-4
1-2
3-4
1-2
1-2
1-2
1-2
3-4
1-2
1-2
3-4
5-6
3-4
3-4
1-2
1-2
1-2
3-4
1-2
1-2
5-6
3-4
1-2
Somewhat disagree
Somewhat agree
Somewhat disagree
Somewhat agree
Somewhat disagree
Somewhat agree
Somewhat disagree
Somewhat agree
Strongly disagree
Strongly disagree
Somewhat agree
Somewhat disagree
Strongly agree
Somewhat disagree
Somewhat agree
Somewhat agree
Somewhat disagree
Somewhat agree
Somewhat agree
Strongly agree
Strongly agree
Somewhat agree
Somewhat agree
Somewhat agree
Strongly agree
Strongly agree
Somewhat agree
Neither agree nor disagree
Somewhat agree
Somewhat disagree
Somewhat disagree
Neither agree nor disagree
Strongly agree
Somewhat agree
Strongly agree
Somewhat disagree
Somewhat agree
Somewhat agree
Somewhat agree
Somewhat agree
Strongly agree
Somewhat agree
Strongly disagree
Strongly disagree
Somewhat disagree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly disagree
Somewhat agree
Strongly disagree
Strongly disagree
Neither agree nor disagree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly disagree
Somewhat disagree
Strongly disagree
Strongly disagree
Somewhat disagree
Strongly agree
Strongly agree
Neither agree nor disagree
Somewhat disagree
Somewhat agree
Somewhat agree
Strongly agree
Somewhat disagree
Somewhat agree
Strongly disagree
Strongly disagree
Strongly disagree
Somewhat disagree
Somewhat disagree
Strongly disagree
Somewhat disagree
Strongly disagree
Strongly disagree
Somewhat disagree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly disagree
1-2
1-2
1-2
1-2
3-4
3-4
3-4
1-2
1-2
5-6
1-2
7+
1-2
7+
3-4
1-2
3-4
1-2
1-2
1-2
1-2
1-2
1-2
3-4
1-2
1-2
1-2
1-2
5-6
5-6
5-6
3-4
5-6
1-2
1-2
5-6
3-4
1-2
5-6
5-6
1-2
1-2
Somewhat disagree
Strongly agree
Strongly agree
Somewhat agree
Somewhat disagree
Strongly agree
Somewhat disagree
Somewhat agree
Somewhat agree
Somewhat disagree
Somewhat disagree
Strongly disagree
Somewhat disagree
Somewhat agree
Somewhat agree
Somewhat disagree
Somewhat disagree
Somewhat agree
Somewhat agree
Strongly disagree
Somewhat agree
Somewhat agree
Somewhat agree
Strongly disagree
Somewhat agree
Somewhat agree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly disagree
Somewhat disagree
Somewhat agree
Strongly disagree
Strongly disagree
Strongly disagree
Strongly disagree
Somewhat agree
1-2
1-2
3-4
1-2
7+
1-2
1-2
3-4
1-2
7+
1-2
3-4
1-2
1-2
3-4
3-4
1-2
1-2
5-6
time/week
SLHS 491 Quantitative (Survey) Data Analysis Project
PART I:
Research Problem:
Over the years there has been an increasingly high demand for speech language pathology
services. Although this increase is embraced by the profession, the added caseload has created
pressure to keep up with expectations placed upon the speech-language pathologists (SLP).
According to ASHA’s 2016 Schools Survey, there is current evidence that caseload affects many
factors within the roles of an SLP in the school setting, creating a difference in case management
within this setting. Caseload requires the effective use of qualitative and quantitative elements
of the services they provide (Kenny and Lincoln, 2012).
With an increase of demand for services came an increase in SLP positions that needed to be
filled. Although higher education programs are providing the world with licensed SLP’s, there is
still a shortage of professionals in the school setting versus medical setting due to various
factors.
“Several factors have been identified as contributing to the shortage of SLPs in the school
environment. Legislation, regulatory issues, professional activities, medical practices, and
demographics have all contributed to changes in the roles and responsibilities of SLPs in school
settings” (Woltmann and Camron, 2009). Over the years the increase in caseload in a school
setting has affected the SLP’s caseload management, client care, and professional well-being to
the extent that they no longer want to fulfill the position within the school and pursue positions
elsewhere (Kenny and Lincoln, 2012).
In addition to caseload numbers, SLPs cite excessive paperwork and lack of time for planning,
collaboration, and meeting with teachers and parents as a major challenge (Woltmann and
Camron, 2009). The purpose of this study was to gain information on school SLP’s experiences
when dealing with caseload, as well as how it affects ability to reach therapy outcomes, SLP’s
daily workload duties, and the differences they see in geographical locations.
Kenny, B.,& Lincoln, M. (2012). Sport, scales, or war? Metaphors speech-language pathologists
use to describe caseload management. International Journal of Speech-Language
Pathology,14(3), 247-259. Doi: 10.3109/17549507.2012.651747
Woltmann, J., & Camron, S. C. (2009). Use of workload analysis for caseload establishment in the
recruitment and retention of school-based speech-language pathologists. Journal of
Disability Policy Studies, 20(3), 178-183.
doi:http://dx.doi.org/10.1177/1044207309343427
Research Question:
What effect does caseload size have on an SLP’s satisfaction with their job
Hypothesis:
There will be an inverse correlation between the size of caseload and the job
satisfaction ratings of school SLPs
SLHS 491 Quantitative (Survey) Data Analysis Project
Participants and Sampling:
To explore the research question investigates the impact of caseload size on school-based
speech language pathologists. The survey was sent to ASHA certified school-based speech
language pathologists across the United States in special interest groups (SIG): 1- Language,
Learning and Education and 16- School Based Issues. Going through ASHA ensures that the
SLP’s are ASHA certified. There is no more than minimal risk for participants.
The participants were selected using the convenience sampling method. The survey implied
included a question to verify that all participants were employed by a school district.
Participants voluntarily participated in the survey and resulted in __ (number of participants). A
survey was developed by the researchers. Based on the submission of the electronic survey,
consent from the participants was implied. The survey was sent to ASHA certified SLPS that are
members in SIG groups in November 2018.
PART II:
Data Analysis
Please calculate:
o The mean, median, and mode for each of the six (6) questions
o Please assign a number to each “Likert level” score prior to calculating the
descriptive statistical measures described above.
▪ Strongly disagree
1
OR
-2
▪ Somewhat disagree
2
OR
-1
▪ Neither agree or disagree
3
OR
0
▪ Somewhat agree
4
OR
1
▪ Strongly agree
5
OR
2
o Determine the relationship (if there is one) between current caseload size (A)
and the responses to the other five (5) questions (B, C, D, E, and F).
o Determine the relationship (if there is one) between (at least) two additional
questions and the responses to the other five (5) questions.
▪ (for example, the relationship between B AND A, C, D, E, and F)
o Calculate individual descriptive statistics as appropriate
Results should be presented in tables, graphs, and/or charts in such a way that the data
“pops” for the reader
PART III:
Results:
Include a summary statement about what you found and whether or not your
hypothesis was supported
PART IV
Conclusions:
Were the results what you expected?
SLHS 491 Quantitative (Survey) Data Analysis Project
Can you identify any extraneous (confounding) variables? How much do you feel that
they influenced your results?
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