BMAL-590 Quantitative Research
Questions and Answers 100% Accurate
What Is Statistics? - ANSWER-"Statistics is a way to get information from data."
Statistics is a tool for creating new understanding from a set of numbers.
You need data and information
descriptive statistics - ANSWER-one of two branches of statistics which focuses on
methods of organizing, summarizing, and presenting data in a convenient and
informative way.
One form of descriptive statistics uses graphical techniques which allow statistics
practitioners to present data in ways that make it easy for the reader to extract useful
information.
Another form of descriptive statistics uses numerical techniques to summarize data.
Rather than providing the raw data, the professor may only share summary data with
the student.
Histogram - ANSWER-(or bar graph) can show if the data is evenly distributed across
the range of values, if it falls symmetrically from a center peak (normal distribution), if
there is a peak but the more of the data falls on one side of the peak than the other (a
skewed distribution), or if there are two or more peaks in the data (bi- or multi-modal).
average - ANSWER-mean
range - ANSWER-calculated by subtracting the smallest number from the largest.
mode - ANSWER-the most frequently occurring score(s) in a distribution
variance - ANSWER-the average squared deviation from the mean
Standard deviation - ANSWER-the square root of the variance and gets the variability
measure back to the same units as the data. Standard deviation has many useful
properties when the data is normally distributed
inferential statistics - ANSWER-a body of methods used to draw conclusions or
inferences about characteristics of populations based on sample data.
Exit polls are a very common application of statistical inference.
,Statistical inference problems involve three key concepts: - ANSWER-population, the
sample, and the statistical inference.
Population: - ANSWER-the group of all items of interest to a statistics practitioner. It is
frequently very large and may, in fact, be infinitely large. In the language of statistics,
population does not necessarily refer to a group of people. It may, for example, refer to
the population of diameters of ball bearings produced at a large plant.
A descriptive measure of a population is called a parameter. In most applications of
inferential statistics, the parameter represents the information we need.
Sample - ANSWER-a set of data drawn from the population. A descriptive measure of a
sample is called a statistic. We use statistics to make inferences about parameters.
statistical inference - ANSWER-the process of making an estimate, prediction, or
decision about a population based on sample data. Because populations are almost
always very large, investigating each member of the population would be impractical
and expensive. It is far easier and cheaper to take a sample from the population of
interest and draw conclusions or make estimates about the population on the basis of
information provided by the sample. However, such conclusions and estimates are not
always going to be correct. For this reason, we build into the statistical inference a
measure of reliability.
A company has developed a new smartphone whose average lifetime is unknown. In
order to estimate this average, 200 smartphones are randomly selected from a large
production line and tested; their average lifetime is found to be 5 years. The 200
smartphones represent a - ANSWER-sample
Which of the following is a measure of the reliability of a statistical inference -
ANSWER-a significance level
The process of using sample statistics to draw conclusions about population parameters
is called - ANSWER-doing inferential statistics
Which of the following statements involve descriptive statistics as opposed to inferential
statistics - ANSWER-The Alcohol, Tobacco and Firearms Department reported that
Houston had 1,791 registered gun dealers in 1997.
There are two such measures, the confidence level and the significance level. The
confidence level is the proportion of times that an estimating procedure will be correct.
When the purpose of the statistical inference is to draw a conclusion about a population,
the significance level measures how frequently the conclusion will be wrong in the long
run.
Statistical inference is the process of making an estimate, prediction, or decision about
a population based on a sample.
, What can we infer about a Population's Parameters based on a Sample's Statistics? -
ANSWER-Since statistical inference involves using statistics to make inferences about
parameters, we can make an estimate, prediction, or decision about a population based
on sample data. We can apply what we know about a sample to the larger population
from which it was drawn!
non-sampling error - ANSWER-more serious than sampling error because taking a
larger sample won't diminish the size, or the possibility of occurrence, of this error. Even
a census can (and probably will) contain non-sampling errors. Non-sampling errors
result from mistakes that are made in the acquisition of data. Non-sampling errors also
result from the sample observations being selected improperly.
Three types of non-sampling errors are errors in: - ANSWER-data acquisition, non-
response errors, and selection bias
Data acquisition - ANSWER-errors arise from the recording of incorrect responses.
Incorrect responses may be the result of incorrect measurements taken because of
faulty equipment, mistakes made during transcription from primary sources, inaccurate
recording of data due to misinterpretation of terms, or inaccurate responses to
questions concerning sensitive issues such as sexual activity or possible tax evasion.
Confidence level - ANSWER-the proportion of times that an estimating procedure will be
correct. A confidence level of 95% means that estimates based on this form of statistical
inference will be correct 95% of the time.
significance level - ANSWER-measures how frequently the conclusion will be wrong in
the long run. A 5% significance level means that, in the long run, this type of conclusion
will be wrong 5% of the time.
𝛼 - ANSWER-Greek letter "alpha"
If we use 𝛼 to represent significance, then our confidence level is 1−𝛼
Confidence Level + Significance Level = 1
Consider a statement from polling data you may hear about in the news: "This poll is
considered accurate within 3.4 percentage points, 19 times out of 20." In this case, our
confidence level is 95% (19/20 = 0.95), while our significance level is 5%. A 5%
significance level means, that in the long run, this type of conclusion will be wrong 5% of
the time.
A population of all college applicants exists who have taken the SAT exam in the United
States in the last year. A parameter of the population are - ANSWER-SAT scores
Data - ANSWER-Facts and statistics collected together for reference or analysis
