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Quantitative Research Methods
Student`s Name
Course
Instructor`s Name
Date
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D3.4.1
D3.4.1a
The mean visualization test score is 5.2433.
D3.4.1b
The skewness statistic for the math achievement test is .044, while the standard error, on
the other hand, is .277. What that tells us is that the math achievement test score presented in the
test score has been distributed normally. That is mainly because of how the skewness statistic
lies between +1 and -1.
D3.4.1c
The minimum score for mosaic pattern score is -4.0. That can directly be compared to the
lowest possible score, which has been presented to the mosaic pattern test. That plays a
significant role in showing us that some of the subjects used in the study have recorded a score of
less than the probable score, which is within the mosaic pattern test. The mosaic pattern has been
used in the study as a particular form of stacked bar chart that has played a critical role in
showing the percentages of the data, which has been categorized into different groups. Therefore,
the plot of the mosaic pattern has been represented graphically in the contingency table. On the
other hand, the variable competence scale presented the skewness statistic as -1.634, which plays
a significant role in demonstrating that the variable failed in following the normal distribution.
D3.4.2
D3.4.2a
For the variables called scale in output 4.1b, the skewness static seems to be less than -1.00 since
it results in -1.634.
D3.4.2b
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The skewness presented is generally asymmetrical in a statistical distribution, which
means that the curve appears either distorted or skewed towards the left or the right. The answer
given under the skewness static is essential mainly because it plays a significant role in
delivering a general overview of the shape of the distribution within the continuous variable.
Once the skewness static results to either more than 1.00 or less than -1.00, then it means that the
distribution of that variable will deviate from the bell-shaped curve, which is not considered part
of the normal distribution. In this case, the variable competence scale is -1.634, meaning that the
distribution never follows a normal distribution.
D3.4.2c
The answer presented is in agreement with the boxplot in output 4.2. That is mainly
because the boxplot for the variable competence scale cannot be considered symmetrical
concerning the median. Therefore, the boxplot presents a clear presentation of how the
distribution of the competence scale has been negatively skewed. Additionally, the box plot also
presents different outliers, which are generally considered lower than the minimum.
D3.4.3
D3.4.3a
Based on the output 4.2b, 4 participants, which totals 5.3%, have missing data.
D3.4.3b
The percentage of students presented in the output 4.2b with either a valid, also referred to as the
non-missing motivation scale, or the competence scale score is 94.7%.
D3.4.3c
From output 4.1, either one or two participants are missing both motivation and
competence scale scores. Other the other hand, from output 4.2b, four participants are missing
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both motivation and competence scale scores. That tells us that the data used in both outputs is
ordinal. That is mainly because the data used can be considered ordinal since they are in the
second level of measurement. The data plays a significant role in reporting the ranking and
ordering of the data without necessarily having to establish the degree of variation between the
participants used in determining the missing participants for both motivation and competence
scale scores. That means that the data used in both outputs is quantitative data in nature which
plays a significant role in the occurring orders, while on the other hand, the difference is not
known. The intensity of the difference between the participants missing both motivation and
competence scale scores can be understood whether the variables are more or less than one.
D.3.4.4
D3.4.4a
The mean presents the percentage of participants which can be categorized in each of the
two categories, which have generally been presented under the dichotomous variables.
Therefore, on the variable Gender, its mean can be considered to be .55, meaning that 55% of the
participants have been coded as 1 (female) while the remaining 45% have been coded as 0
(male). That means there are a higher number of females than males since their mean is higher
than .5.
The mean for variable Algebra is .47, meaning that 53% of the participants do not have
Algebra. In comparison, 47% have algebra 2 in H.S hence meaning that there are fewer students
with Algebra 1 in H.S. The variable Geometry has a mean of 48 hence meaning that 52% of the
participants fail to have Geometry in H.S. In comparison, the remaining 48% have Geometry in
H.S. The mean for variable Math Grades is .41 meaning that 59% do not have math grades. The
mean for Calculus is 0, meaning that Algebra 1 is close to 1. The mean for Calculus is .11
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totaling 11%, meaning that the remaining 89% do not have Calculus in H.S. The mean for
Algebra 1 is .79, which totals 79%, meaning that the remaining 21% do not have Algebra 1 in
H.S hence meaning that there are more students with Algebra 1 H.S since it is more than 5.
D3.4.4b
75 participants are there altogether.
D3.4.4c
The number of participants that completed the data is 75 participants.
D3.4.4d
45% of the total participants are mal the fast track.
D3.4.4e
The total percentage of participants that took Algebra 1 H.S is 79%.
D.3.4.5
D3.4.5a
9.6% of the single listed group are Asian-Americans.
D3.4.5b
8% of the total number of students have a visualization two scores of 6%.
D3.4.5c
7% of the total number of students have a visualization score of 6 or less.
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References
Leech, N., Barrett, K. C. Morgan, G. A. (2005). SPSS for Intermediate Statistics; Use and
Interpretation. Lawrence Erlbaum Associates, Inc.: Mahwah, NJ.
Morgan, G. A., Leech, N., Gloeckner, G., Barrett, K. C. (2013). IBM SPSS for Introductory
Statistics (5th Ed.). Routledge: New York, NY
