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choose a data that research interests, taking into consideration that the data consists qualitative and quantitative variables. (using the available data sources, i.e. questionnaire, records, approved electronic sites, ....etc.)
please solve it clearly and make sure it's correct 100%
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Answer:
A variable is a characteristic of an object. Their values may occur more than once for a set of data. We consider just two main types of variables in this course.
Quantitative Variables - Variables whose values result from counting or measuring something.
Examples: height, weight, time in the 100 yard dash, number of items sold to a shopper
Qualitative Variables - Variables that are not measurement variables. Their values do not result from measuring or counting.
Examples: hair color, religion, political party, profession
Designator - Values that are used to identify individuals in a table. Designator values usually do not repeat in a table, but variable values often do repeat.
Qualitative Methods |
Quantitative Methods |
Methods include focus groups, in-depth interviews, and reviews of documents for types of themes |
Surveys, structured interviews & observations, and reviews of records or documents for numeric information |
Primarily inductive process used to formulate theory or hypotheses | Primarily deductive process used to test pre-specified concepts, constructs, and hypotheses that make up a theory |
More subjective: describes a problem or condition from the point of view of those experiencing it | More objective: provides observed effects (interpreted by researchers) of a program on a problem or condition |
Text-based | Number-based |
More in-depth information on a few cases | Less in-depth but more breadth of information across a large number of cases |
Unstructured or semi-structured response options | Fixed response options |
No statistical tests | Statistical tests are used for analysis |
Can be valid and reliable: largely depends on skill and rigor of the researcher | Can be valid and reliable: largely depends on the measurement device or instrument used |
Time expenditure lighter on the planning end and heavier during the analysis phase | Time expenditure heavier on the planning phase and lighter on the analysis phase |
Less generalizable | More generalizable |
Examples: name, rank, jersey number of a team member, cell phone number, license number.
It is important to identify whether the data are quantitative or
qualitative as this affects the statistics that can be
produced.
Frequency counts:
The number of times an observation occurs (frequency) for a data
item (variable) can be shown for both quantitative and qualitative
data.
The graphs below arrange the quantitative and qualitative data to
show the frequency distribution of the data.
Quantitative Data
Qualitative Data
As absolute frequencies can be calculated on quantitative and
qualitative data, relative frequencies can also be produced, such
as percentages, proportions, rates and ratios. For example, the
graphs above show 4 people (20%) worked less than 30 hours per
week, and 6 people (30%) are teachers.
Descriptive (summary) statistics:
Statistics that describe or summarise can be produced for
quantitative data and to a lesser extent for qualitative
data.
As quantitative data are always numeric they can be ordered, added
together, and the frequency of an observation can be counted.
Therefore, all descriptive statistics can be calculated using
quantitative data.
As qualitative data represent individual (mutually exclusive)
categories, the descriptive statistics that can be calculated are
limited, as many of these techniques require numeric values which
can be logically ordered from lowest to highest and which express a
count.
Mode can be calculated, as it it the most frequency observed value.
Median, measures of shape, measures of spread such as the range and
interquartile range require an ordered data set with a logical
low-end value and high-end value. Variance and standard deviation
require the mean to be calculated, which is not appropriate for
categorical variables as they have no numerical value.
Inferential statistics:
By making inferences about quantitative data from a sample,
estimates or projections for the total population can be
produced.
Quantitative data can be used to inform broader understandings of a
population, or to consider how that population may change or
progress into the future.
For example, a simple income projection for an employee in 2015 may
be inferred from the rate of change for data collected in 2000,
2005, and 2010.
As shown in the graph below, data collected over time indicates a
5% increase every five years. Therefore, if the rate of increase
continues to follow the same pattern, it can be projected that the
annual income for that employee in 2015 will be $46,305; which is
the 2010 wage of $44,100 increased by an additional 5%.
Qualitative data are not compatible with inferential statistics as
all techniques are based on numeric values.
Exercises: In the tables below identify which columns represent qualitative variables, which columns represent quantitative variables, and which columns represent designators.
1) Highest U.S. Dams
Name |
Height |
River |
State |
Completed |
Oroville |
754 |
Feather |
CA |
1968 |
Hoover |
725 |
Colorado |
NV |
1936 |
Dworshak |
718 |
N Fork Clearwater |
ID |
1873 |
Glen Canyon |
708 |
Colorado |
AZ |
1966 |
New Bullards Bar |
636 |
North Yuba |
CA |
1970 |
New Melones |
626 |
Stanislaus |
CA |
1979 |
Swift |
610 |
Lewis |
WA |
1958 |
Mossyrock |
607 |
Cowlitz |
WA |
1968 |
Shasta |
600 |
Sacramento |
CA |
1945 |
Hungry Horse |
564 |
S Fork Flathead |
MT |
1953 |
Grand Coulee |
551 |
Columbia |
WA |
1942 |
Ross |
541 |
Skagit |
WA |
1949 |
Source: The World Almanac and Book of Facts 1998
2) Super Bowls
No. |
Year |
Winner |
Winning Score |
Loser |
Losing Score |
Winning Coach |
Game Site |
I |
1967 |
Packers |
35 |
Chiefs |
10 |
Lombardi |
Los Angeles |
II |
1968 |
Packers |
33 |
Raiders |
14 |
Lombardi |
Miami |
III |
1969 |
Jets |
16 |
Colts |
7 |
Ewbank |
Miami |
IV |
1970 |
Chiefs |
23 |
Vikings |
7 |
Stram |
New Orleans |
V |
1971 |
Colts |
16 |
Cowboys |
13 |
McCafferty |
Miami |
VI |
1972 |
Cowboys |
24 |
Dolphins |
3 |
Landry |
New Orleans |
VII |
1973 |
Dolphins |
14 |
Redskins |
7 |
Shula |
Los Angeles |
VIII |
1974 |
Dolphins |
24 |
Vikings |
7 |
Shula |
Houston |
IX |
1975 |
Steelers |
16 |
Vikings |
6 |
Noll |
Miami |
X |
1976 |
Steelers |
21 |
Cowboys |
17 |
Noll |
Pasadena |
XI |
1977 |
Raiders |
32 |
Vikings |
14 |
Madden |
New Orleans |
Source: The World Almanac and Book of Facts 1998
ANSWER:
Accuracy and Scientific Notation
1) 0 places, 3 sig. digits, 5.42 x 104 |
2) 0 places, 5 sig. digits, 1.7846 x 108 |
||
3) 7 places, 4 sig. digits, 2.314 x 10-4 |
4) 5 places, 3 sig. digits, 9.80 x 10-3 |
||
5) 3 places, 6 sig. digits, 1.32502 x 102 |
6) 2 places, 4 sig. digits, 3.741 x 101 |
||
7) 4 places, 4 sig. digits, 3.473 x 10-1 |
8) 1 place, 5 sig. digits, 1.4453 x 103 |
||
9) 4.897 |
10) 245.12 |
11) 83.1 |
12) 0.432 |
13) 110 |
14) 27.34 |
15) 539,500 |
16) 4,390,000 |
17) 0.00435 |
18) 0.0006288 |
19) 57,789 |
20) 312,200 |
21) 0.008324 |
22) 0.0000769 |
Comparing Modified Boxplots
1) |
8 AM is more skewed, 9 AM has largest value, 9 AM has smallest value, 8 AM has largest median, 9 AM has largest range, 9 AM has largest IQR |
2) |
11 AM is more skewed, 10 AM has largest value, 11 AM has smallest value, 10 AM has largest median, the ranges are the same and 11 AM has largest IQR. |
3) |
1 PM is more skewed, the largest values are about the same, 2 PM has the smallest value, 1 PM has largest median, 2 PM has the largest range and largest IQR. |
4) |
3 PM is more skewed, 3 PM has largest value, 4 PM has smallest value, 3 PM has largest median, 4 PM has the largest range and IQR. |
5) |
5 PM is more skewed, 5 PM has largest value, 6 PM has smallest value, 5 PM has largest median, 5 PM has the largest range, the IQR's are about the same. |
Computing Formula Values
1) 74.08 |
2) 55.73 |
3) 0.4733 |
4) 0.1475 |
5) 2.72 |
6) -0.85 |
7) -0.7171 |
8) 0.7191 |
9) 1,637,000 |
10) 265,400 |
11) 295.6 |
12) 94.88 |
Coefficients of Determination and Correlation
1) 45.2% of the variation is explained by the regression line. |
|
2) 91.3% of the variation is explained by the regression line. |
|
3) 72.1% of the variation is explained by the regression line. |
|
4) 26.4% of the variation is explained by the regression line. |
|
5) weak positive correlation |
6) no correlation |
7) strong positive correlation |
8) perfect negative correlation |
9) moderate positive correlation |
10) moderate negative correlation |
11) no correlation |
12) strong negative correlation |
Grouped Data
1) mean = 32.2, std. dev. = 11.1 |
2) mean = 10.7, std. dev. = 9.6 |
3) mean = 15.6, std. dev. = 10.8 |
4) mean = 21.1, std. dev. = 11.7 |
5) mean = 44.0, std. dev. = 10.6 |
6) mean = 80.5, std. dev. = 8.1 |
7) mean = 36.8, std. dev. = 7.6 |
8) mean = 31.6, std. dev. = 5.2 |
Histogram Analysis
1) |
minimum = 18, maximum = 60, skewed left, one peak at 45,one gap between 24 and 30, no extreme values |
2) |
minimum = 12, maximum = 108, skewed left, two peaks at 54 and 90, one gap between 24 and 36, no extreme values |
3) |
minimum = 0, maximum = 500, skewed right, one peak at 25, 3 gaps: between 100 and 150, between 200 and 250, and between 300 and 400. Since the last gap is twice as large, values between 400 and 500 are extreme. |
4) |
minimum = 15, maximum = 40, skewed right, two peaks at 27.5 and 37.5 (but the second peak is barely a peak), no gaps or extreme values. |
Outliers and Influential Observations
1) outlier near (12.9, 24.4), influential observation near (9.9, 16.1) |
2) outlier near (112, 86), influential observation near (129, 121) |
3) outlier near (53, 88), influential observations near (68, 108) and (76, 111) |
Parameters and Statistics
1) |
The parameter is the average height of all women aged 20 years or older. |
The statistic is the average height of 63.9 inches from the sample of 45 women. |
|
2) |
The parameter is the mean amount of sodium consumed by children under the age of ten. |
The statistic is the mean of 2993 milligrams of sodium obtained from the sample of 75 children. |
|
3) |
The parameter is the proportion of patients healed by Nexium in 8 weeks. |
The statistic is 213/224 = 0.951, the proportion healed in the sample. |
|
4) |
The parameter is the average farm size in Kansas. |
The statistic is the mean farm size of 731 acres from the sample of 40 farms. |
|
5) |
The parameter is the average oil output per well in the United States. |
The statistic is the mean oil output of 10.7 barrels per day from the sample of 50 wells. |
|
6) |
The parameter is the proportion of adults 18 or older who read a book in the previous year. |
The statistic is 835/1006 = 0.830, the proportion who read a book in the sample. |
|
7) |
The parameter is the average amount of calcium that male teenagers consume. |
The statistic is the mean of 1081 milligrams of calcium from the sample of 50 teenagers. |
|
8) |
The parameter is the proportion of adults with kids under 18 who ate together 7 days a week. |
The statistic is 337/1122 = 0.300, the proportion in the sample who ate together. |
|
9) |
The parameter is the mean verbal SAT score for students whose first language is not English. |
The statistic is the mean SAT verbal score of 458 from the sample of 20 students. |
Qualitative vs. Quantitative
1) |
Name - designator, Height - quantitative, River - qualitative, State - qualitative, Completed - quantitative |
2) |
Related Solutionschoose a data that research interests, taking into consideration that the data consists qualitative and quantitative...choose a data that research interests, taking into consideration
that the data consists qualitative and quantitative variables.
(using the available data sources, i.e. questionnaire, records,
approved electronic sites, ....etc.)
the data should be entered in a table
please
choose a data that research interests, taking into consideration that the data consists qualitative and quantitative...choose a data that research interests, taking into consideration
that the data consists qualitative and quantitative variables.
(using the available data sources, i.e. questionnaire, records,
approved electronic sites, ....etc.)
please solve it clearly and make sure it's correct
100%
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a quantitative design and a qualitative design and putting them
together? explain the types of research questions served by methods
research. explain one strength and one limitation of mixed methods
research. Finally, provide a rationale for or against the utility
of mixed methods research in your discipline
Discuss the value and use of quantitative and qualitative research and data in business. Articulate the...Discuss the value and use of quantitative and qualitative
research and data in business. Articulate the difference between
the two types of research and provide specific examples of when
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setting.
Discuss sources of bias for both quantitative and qualitative research. For quantitative research, be sure to...Discuss sources of bias for both quantitative and qualitative
research. For quantitative research, be sure to address both random
and systematic bias. You may use examples from the articles you
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facts about qualitative and quantitative research methods.facts about qualitative and quantitative research methods.
What is the overall difference between qualitative research studies and quantitative research studies? Why are qualitative...
What is the overall difference between qualitative research
studies and quantitative research studies?
Why are qualitative studies typically not generalizable from
the sample to the population of study
3.Why are applied studies typically not generalizable from the
sample to the population of study?
Explain why there are no independent/dependent variables in
qualitative research studies?
What purpose does theory serve in research and if the article
states a theory where would you find it?
When do you use a quantitative and qualitative research
When do you use a quantitative and qualitative research
State the differences between: Conceptual Research and Empirical Research. Quantitative Research and Qualitative Research. Research Method...State the differences
between:
Conceptual Research and Empirical Research.
Quantitative Research and Qualitative Research.
Research Method and Research
Methodology.
Your answer should not accessed 250 words for each
request.
explain 5 advantages and 5 disadvantages of quantitative and qualitative researchexplain 5 advantages and 5 disadvantages of quantitative and
qualitative research
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