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Those unaware of how the process works may not see much value in applying statistical knowledge to any of the vast array of topics in the study of biology, but today we’ll be taking a look at how biostatistics works and what its different applications are. Let’s see how well you know the topic!
Questions and Answers
1.
_________ is a collection of procedures and principles for gathering data and analyzing information to help people make decisions when faced with uncertainty.
A.
Data
B.
Parameter
C.
Statistics
D.
Sample
Correct Answer C. Statistics
Explanation Statistics is a collection of procedures and principles for gathering data and analyzing information to help people make decisions when faced with uncertainty. It involves the collection, organization, analysis, interpretation, and presentation of data. By using statistical methods, patterns, trends, and relationships within the data can be identified, allowing for informed decision-making. Statistics is essential in various fields such as business, economics, healthcare, and social sciences, where data-driven insights are necessary for making informed choices and predictions.
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2.
___________ referring to numbers or nonnumerical labels (male/female) collected from a set of entities (people, cities, etc)
A.
Data
B.
Variables
C.
Sample
D.
Statistics
Correct Answer A. Data
Explanation Data refers to numbers or nonnumerical labels collected from a set of entities (people, cities, etc). It can include any type of information that is collected and recorded for analysis or reference purposes. This can range from numerical measurements such as age or height to nonnumerical labels such as gender or occupation. Data is a fundamental concept in statistics and is used to derive meaningful insights and make informed decisions.
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3.
Five-number summary
A.
Cut-off points for 1/5
B.
Lowest value
C.
Cut-off points for 1/3
D.
Cut-off points for 1/4
E.
Cut-off points for 1/2
F.
Cut-off points 4/5
G.
Cut-off points 3/4
H.
Highest value
Correct Answer(s) B. Lowest value D. Cut-off points for 1/4 E. Cut-off points for 1/2 G. Cut-off points 3/4 H. Highest value
Explanation The correct answer includes the lowest value, the cut-off points for 1/4, 1/2, and 3/4, and the highest value. The five-number summary consists of these five values and is used to summarize the distribution of a dataset. The lowest value represents the smallest observation in the dataset, the cut-off points for 1/4, 1/2, and 3/4 divide the dataset into four equal parts, and the highest value represents the largest observation in the dataset. Together, these values provide a concise summary of the dataset's range, central tendency, and spread.
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4.
The 3 middle values of the summary are called________
A.
Lower quartile
B.
Extremes
C.
Median
D.
Mode
E.
Highest quartile
F.
Upper quartile
Correct Answer(s) A. Lower quartile C. Median F. Upper quartile
Explanation The 3 middle values of the summary are called the lower quartile, median, and upper quartile. The lower quartile represents the 25th percentile, dividing the data into the bottom 25%. The median is the middle value, dividing the data into two equal halves. The upper quartile represents the 75th percentile, dividing the data into the top 25%. These three values are used to understand the central tendency and distribution of the data.
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5.
Median of a numerical list of data is the value ____________
A.
The sum of the values
B.
Sum of all the values divided by the total number
C.
In the middle when the numbers are put in order
Correct Answer C. In the middle when the numbers are put in order
Explanation The median of a numerical list of data is the value that falls in the middle when the numbers are put in order. This means that if the data set is arranged in ascending or descending order, the median will be the value that separates the lower half of the data from the upper half. It is not affected by the sum of the values or the total number of values in the data set.
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6.
The _______ and __________ are (roughly) the medians of the lower and upper halves of the data
A.
Lower quartile; median
B.
Lower quartile; mode
C.
Mode; higher quartile
D.
Lower quartile; upper quartile
Correct Answer D. Lower quartile; upper quartile
Explanation The lower quartile and upper quartile are (roughly) the medians of the lower and upper halves of the data. The lower quartile represents the median of the lower half of the data, while the upper quartile represents the median of the upper half of the data. These quartiles divide the data into four equal parts, with 25% of the data falling below the lower quartile, 25% falling above the upper quartile, and 50% falling between the two quartiles.
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7.
_________________ helps us see the pattern in the data
A.
Histogram
B.
Dotplot
C.
Steam and leaf plot
Correct Answer B. Dotplot
Explanation A dotplot helps us see the pattern in the data by representing each data point as a dot along a number line. The dots are stacked vertically above their corresponding values, allowing us to easily visualize the distribution and identify any clusters or gaps in the data. This type of plot is especially useful for small data sets or when we want to compare multiple groups side by side. A histogram, on the other hand, uses bars to represent the frequency or proportion of data within certain intervals, while a stem and leaf plot displays the individual data points in a tabular format.
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8.
_________are observations (such as measurements, genders, survey responses) that have been collected
A.
Variables
B.
Samples
C.
Population
D.
Data
Correct Answer D. Data
Explanation Data refers to the observations or information that has been collected. This can include measurements, genders, survey responses, or any other type of collected information. It is the raw material from which conclusions and insights can be drawn. Variables, samples, and population are related concepts, but they do not encompass the full scope of collected observations. Therefore, the correct answer is data.
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9.
Data is lso defined as ____________ recorded information to help minimize uncertainty in decision process
A.
Systematically
B.
Parameter
C.
Statsitic
D.
Vairablly
Correct Answer A. Systematically
Explanation Data is systematically defined as recorded information to help minimize uncertainty in the decision-making process. This means that data is organized and collected in a methodical and structured manner, ensuring that it is reliable and can be used effectively to support decision-making. By gathering data systematically, it becomes easier to analyze and interpret the information, ultimately reducing uncertainty and improving the quality of decisions made based on that data.
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10.
Data uses the 5 Ws and 1 GH
A.
Who, What, When, Where, Why, and How
B.
Who, Would, Why, Where, and How
C.
Who, What, Why, Won't, and How
Correct Answer A. Who, What, When, Where, Why, and How
Explanation The correct answer is "Who, What, When, Where, Why, and How". This answer is correct because the 5 Ws (Who, What, When, Where, and Why) and 1 GH (How) are commonly used to gather information and understand the complete picture of a situation or event. These questions cover the essential aspects of any given data, allowing for a comprehensive analysis and understanding. The inclusion of "Won't" in one of the options is incorrect and does not align with the standard 5 Ws and 1 GH framework.
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11.
__________are collected when all individuals in a population are measured
A.
Sample Data
B.
Population Data
C.
Numerical Data
Correct Answer B. Population Data
Explanation Population data refers to data that is collected when all individuals in a population are measured. This means that data is collected from every member of the population, rather than just a subset or sample. This type of data provides a comprehensive view of the entire population and allows for accurate analysis and conclusions to be drawn. In contrast, sample data refers to data that is collected from a subset of the population, while numerical data simply refers to data that consists of numbers.
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12.
__________a are collected from a subset of a large population.
A.
Numerical Data
B.
Population Data
C.
Sample Data
Correct Answer C. Sample Data
Explanation The term "sample data" refers to a subset of a large population that is collected for analysis or study. In this case, the blanks are being filled with "sample data" to complete the sentence.
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13.
_________ are characteristics recorded about each individual. the_____ should have a name that identify What has been measured.
A.
Data
B.
Units
C.
Variables
D.
Subunits
Correct Answer C. Variables
Explanation Variables are characteristics recorded about each individual. The name of the variable should identify what has been measured.
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14.
________ of data are excellent tools for obtaining preliminary impressions and insights
–Type of ______ depends on type of variables
A.
Visual displays
B.
Rate
C.
Graph
D.
Histograph
Correct Answer A. Visual displays
Explanation Visual displays are excellent tools for obtaining preliminary impressions and insights because they allow us to represent data in a visual format, making it easier to identify patterns, trends, and relationships. Different types of visual displays can be used depending on the type of variables being analyzed. For example, graphs are commonly used for displaying numerical data, while histographs are used for displaying data that is divided into intervals or categories. By using visual displays, we can quickly and effectively summarize and interpret data, leading to a better understanding of the information at hand.
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15.
____________ at which something occurs is simply the number of times it occurs per number of opportunities for it to occur
A.
Risk
B.
Base rate
C.
Baseline risk
D.
Rate
Correct Answer D. Rate
Explanation The given correct answer is "rate". In this context, the rate refers to the frequency or number of times something occurs within a specific period or in relation to a given opportunity. It is a measure of how often an event or action takes place in relation to the total number of opportunities or occurrences.
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16.
_____ of a bad outcome in the future can be estimated by using the past rate for tat outcome, if it is assumed the future will be like the past
A.
Risk
B.
Data
C.
Rate
D.
Variable
Correct Answer A. Risk
Explanation The given statement suggests that the estimation of the likelihood of a negative outcome in the future can be determined by analyzing the past rate of occurrence for that particular outcome. This estimation is based on the assumption that the future will follow a similar pattern as the past. Therefore, the correct answer is "risk" as it refers to the potential for a negative outcome or loss.
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17.
____________ or __________ is the rate of risk at a beginning of a period or under specific conditions
A.
Base rate; baseline rate
B.
Baseline risk; baseline rate
C.
Base risk; baseline rate
Correct Answer A. Base rate; baseline rate
Explanation The correct answer is base rate; baseline rate. The base rate or baseline rate refers to the rate of risk at the beginning of a period or under specific conditions. This term is commonly used in finance and insurance to determine the initial level of risk before any adjustments or modifications are made. It serves as a reference point for evaluating changes in risk over time or in different circumstances.
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18.
•Values measured in groups or categories
•
•Examples:
–Gender
–Favorite color
–Type of car
–Satisfactory rating
A.
Nominal
B.
Categorical
C.
Sample
D.
Qualitative
Correct Answer(s) B. Categorical D. Qualitative
Explanation The given answer is "Categorical, Qualitative". This is because the examples provided (gender, favorite color, type of car, satisfactory rating) are all values that are measured in groups or categories. Categorical data refers to data that can be divided into distinct groups or categories, and qualitative data refers to data that describes qualities or characteristics rather than quantities. Therefore, "Categorical, Qualitative" accurately describes the nature of the values mentioned in the question.
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19.
•Values measured in numeric values with meaning (units/counts)
•
•Examples:
–# of minutes
–weight (in pounds)
–snowfall (in inches)
A.
Nominal
B.
Quantitative
C.
Qualitative
D.
Measurement
Correct Answer(s) B. Quantitative D. Measurement
Explanation The given answer is "Quantitative, Measurement". This is because the examples provided (# of minutes, weight in pounds, snowfall in inches) are all measurements that can be expressed in numeric values with units. This indicates that they are quantitative measurements, which involve the use of numbers to represent quantities or amounts. Therefore, the correct answer is "Quantitative, Measurement".
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20.
Two types of Variables
A.
Qualitative
B.
Quantitative
C.
Nominal
D.
Ordinal
Correct Answer(s) A. Qualitative B. Quantitative
Explanation The given answer is correct because it accurately identifies the two types of variables, which are qualitative and quantitative. Qualitative variables are categorical in nature and represent qualities or characteristics, while quantitative variables are numerical and represent quantities or measurements. The answer also correctly identifies two subtypes of qualitative variables, which are nominal (categories with no inherent order) and ordinal (categories with a specific order or ranking).
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21.
Two types of Categorical variables
A.
Ordinal Variables
B.
Continuous Variables
C.
Discrete Variables
D.
Nominal Variables
Correct Answer(s) A. Ordinal Variables D. Nominal Variables
Explanation The given answer is correct because it correctly identifies two types of categorical variables. Ordinal variables are categorical variables that have a natural order or ranking, such as rating scales or levels of education. Nominal variables, on the other hand, are categorical variables that do not have a natural order or ranking, such as eye color or gender. Therefore, the answer accurately identifies both ordinal variables and nominal variables as two types of categorical variables.
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22.
Two types of Quantitative variables
A.
Nominal Variables
B.
Continuous Variables
C.
Discrete Variables
D.
Ordinal Variables
Correct Answer(s) B. Continuous Variables C. Discrete Variables
Explanation The given answer is correct because it correctly identifies two types of quantitative variables. Continuous variables are those that can take on any value within a certain range, such as height or weight. Discrete variables, on the other hand, can only take on specific values, such as the number of children in a family or the number of cars owned by a person. Therefore, the answer includes both continuous and discrete variables as two distinct types of quantitative variables.
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23.
(one answer)
•Categorical variable where the categories have a natural or logical ordering or ranking
•Examples:
–t-shirt size (S,M,L,XL)
–Satisfaction Rating (very satisfied, somewhat satisfied, somewhat dissatisfied, very dissatisfied)
A.
Ordinal Variables
B.
Discrete Variables
C.
Continuous Variables
D.
Nominal Variables
Correct Answer A. Ordinal Variables
Explanation Ordinal variables are categorical variables where the categories have a natural or logical ordering or ranking. This means that the categories can be arranged in a specific order or sequence. Examples of ordinal variables include t-shirt size (S, M, L, XL) and satisfaction rating (very satisfied, somewhat satisfied, somewhat dissatisfied, very dissatisfied).
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24.
(one answer)
•There is no necessary relationship between the categories. (ie: no natural ordering)
•Names, numbers, or other symbols used to specify the groups to which various subjects belong
•Examples: blood type, gender, marital status
A.
Nominal Variables
B.
Ordinal Variables
C.
Discrete Variables
D.
Continuous Variables
Correct Answer A. Nominal Variables
Explanation The correct answer is Nominal Variables because nominal variables are used to specify the groups to which various subjects belong. Nominal variables do not have a natural ordering or relationship between the categories. Examples of nominal variables include blood type, gender, and marital status.
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25.
(one answer)
•You can actually count the possible responses
•
•Key: number of
•
•Examples:
–# of children
–# of students
–# of pages in book
–# of rooms in house
A.
Continuous Variables
B.
Discrete Variables
C.
Ordinal Variables
D.
Nominal Variables
Correct Answer B. Discrete Variables
Explanation The given correct answer is "Discrete Variables". This is because the examples provided, such as the number of children, number of students, number of pages in a book, and number of rooms in a house, represent variables that can only take on specific, distinct values. In other words, these variables cannot have values between the whole numbers.
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26.
(one answer)
••Can be anything within a given range
•
•Key: amount of
•
•Examples:
–Height/weight
–GPA
–square footage of building
–distance
A.
Nominal Variables
B.
Ordinal Variables
C.
Discrete Variables
D.
Continuous Variables
Correct Answer D. Continuous Variables
Explanation Continuous variables are variables that can take on any value within a given range. They are not limited to specific categories or values, and can include measurements such as height, weight, GPA, square footage of a building, or distance. These variables can be measured on a continuous scale, allowing for a wide range of values.
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27.
•Categorical (nominal) variables with exactly one individual in each category.
Examples: Social Security Number, ISBN, etc
•Be careful not to consider all variables with one case per category (i.e.: year) as ____________
A.
Identifier variables
B.
Discrete Variables
C.
Continuous Variables
D.
Ordinal Variables
Correct Answer A. Identifier variables
Explanation The given correct answer is "Identifier variables". This is because the examples provided, such as Social Security Number and ISBN, are unique identifiers that have exactly one individual in each category. These variables are used to uniquely identify each case or record in a dataset. It is important to distinguish them from other variables, such as categorical variables with multiple individuals in each category or variables that represent different levels of a certain attribute.
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28.
You can analyse Identifier Variables
A.
True
B.
False
Correct Answer B. False
Explanation The statement "you can analyze Identifier Variables" is false. Identifier variables are used to store values in a program, and they are not meant to be analyzed. Instead, they are used to represent data and perform operations on that data. Analysis is typically done on the data stored in identifier variables, not on the variables themselves. Therefore, the given statement is incorrect.
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29.
Good Statistical Displays
A.
Data should stand out clearly from background.
B.
Scale of each axis, including ending point
C.
Source for the data
D.
Keep chart junk
E.
As little “chart junk” as possible
F.
Figures or tables should have a somewhat clear title or purpose
G.
Clear labeling of Title or purpose of picture.
H.
Scale of each axis, including starting point
I.
What each axis, bar, pie segment etc denotes
Correct Answer(s) A. Data should stand out clearly from background. E. As little “chart junk” as possible G. Clear labeling of Title or purpose of picture. H. Scale of each axis, including starting point I. What each axis, bar, pie segment etc denotes
Explanation The answer includes several important factors for good statistical displays. Data should stand out clearly from the background, which helps ensure that it is easily distinguishable. It is also important to minimize "chart junk," which refers to unnecessary elements that can clutter the display and distract from the data. Clear labeling of the title or purpose of the picture helps provide context and understanding. Additionally, the scale of each axis, including the starting and ending points, should be clearly indicated. Lastly, it is important to clearly indicate what each axis, bar, pie segment, etc. represents in order to avoid confusion.
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30.
Displaying Categorical Data with Tables and Graphs...
A.
Relative Frequency Table (1 or more variables)
B.
Bar Graph (1 or more variables)
C.
Pie Chart (1 variable)
D.
Bar Graph (1 variable)
E.
Relative Frequency Table (1 variable)
F.
Pie Chart (1 or more variable)
G.
Contingency Tables (2 variables)
H.
Contingency Tables (1 variables)
Correct Answer(s) B. Bar Graph (1 or more variables) C. Pie Chart (1 variable) E. Relative Frequency Table (1 variable) G. Contingency Tables (2 variables)
Explanation The correct answer is a combination of different methods for displaying categorical data. A bar graph is used when there is one or more variables, as it allows for easy comparison between categories. A pie chart is used when there is only one variable, as it shows the proportion of each category in relation to the whole. A relative frequency table is used when there is one variable, as it displays the frequencies of each category as a proportion of the total. Finally, contingency tables are used when there are two variables, as they show the relationship between two categorical variables.
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31.
Univariate means....
A.
One varaible
B.
2 variables
C.
More than two varaibles
Correct Answer A. One varaible
Explanation Univariate means having only one variable. It refers to a statistical analysis or study that focuses on a single variable at a time, examining its characteristics, distribution, and relationships with other variables. In univariate analysis, data is analyzed and summarized using measures such as mean, median, mode, and standard deviation for a single variable, without considering the influence of other variables.
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32.
_______ for a properly conducted survey is a number that is added to and subtracted from the sample information to produce an interval that is 95 % certain to contain the true value for the population
A.
Margin of sample error
B.
Poll
C.
Margin of error
D.
Sample survey
Correct Answer C. Margin of error
Explanation The margin of error for a properly conducted survey is a number that is added to and subtracted from the sample information to produce an interval that is 95% certain to contain the true value for the population. This means that if the survey was conducted multiple times, the true value for the population would fall within this interval 95% of the time. The margin of error accounts for the inherent variability and uncertainty in sampling, and provides a measure of the precision and reliability of the survey results.
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33.
__________ or ______ the investigators gather opinions or other information from each individual included in the sample.
A.
Poll; margin of error
B.
Margin or error; sample margin of error
C.
Poll; sample survey
D.
Sample survey; sample margin of error
Correct Answer C. Poll; sample survey
Explanation In order to gather opinions or other information from each individual included in the sample, the investigators would conduct a poll to collect data from a specific group of people. Additionally, they would conduct a sample survey to collect data from a smaller subset of the population in order to estimate the characteristics of the larger population.
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34.
In some polls the margin of error is called ________ to distinguish it from other sources of errors and biases that can distort the result
Correct Answer sample margin of error
Explanation The term "sample margin of error" is used in some polls to specifically refer to the margin of error, which is the range within which the true population value is likely to fall. This term is used to differentiate it from other sources of errors and biases that can affect the accuracy of the poll results. By specifying "sample" in the term, it emphasizes that the margin of error is based on the sample data collected and may not accurately represent the entire population.
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35.
Magazines, tv stations, and internet websites routinely conduct this kind of poll, and those who respond are called _____________ or___________
A.
Volunteer sample
B.
Self-esteemed sample
C.
Self-selected sample
D.
Participating sample
Correct Answer(s) A. Volunteer sample C. Self-selected sample
Explanation Magazines, TV stations, and internet websites often conduct polls where individuals voluntarily choose to participate and respond. These individuals are referred to as a "volunteer sample" or a "self-selected sample" as they have willingly chosen to take part in the poll.
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36.
_____________ can occur when many people who are selected for the sample either do not respond at all or do not respond to some of the key survey questions
A.
Participation bais
B.
Response bias
C.
Volunteer sample
D.
Nonparticipation bais
Correct Answer D. Nonparticipation bais
Explanation Nonparticipation bias can occur when many people who are selected for the sample either do not respond at all or do not respond to some of the key survey questions. This can lead to a skewed representation of the population being studied, as the non-respondents may have different characteristics or opinions compared to those who do participate. Therefore, the results may not accurately reflect the true population, introducing bias into the findings.
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37.
Nonparticipation bias is also called
A.
Response bias
B.
nonresponse bias
Correct Answer B. nonresponse bias
Explanation Nonparticipation bias refers to the tendency for certain individuals or groups to not participate in a study, which can result in a biased sample. This bias can occur due to various reasons such as refusal to participate, inability to be reached, or non-completion of the study. Nonresponse bias is a term used interchangeably with nonparticipation bias, as it refers to the bias that arises when those who do not respond to a survey or study differ from those who do respond in important ways. Therefore, the correct answer for this question is nonresponse bias.
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38.
___________ is one in which participants are merely observed and measure
A.
Observational study
B.
Randomized experiment
C.
Treatment
D.
Confounding variable
Correct Answer A. Observational study
Explanation An observational study is a type of research method where participants are only observed and measured without any intervention or manipulation of variables. In this study, researchers do not assign treatments or control groups, but rather collect data by observing and recording the natural behavior or characteristics of the participants. This type of study is useful for exploring relationships between variables and identifying patterns or trends, but it cannot establish causation.
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39.
Creating Frequency Table for categorical variables....
A.
Identify Different Categories/ Tally the amount that falls into each category place in table/ Create Frequency column/ Relative Frequency column ( frequency / n) / convert into%
B.
Identify Different Categories/ Tally the amount that falls into each category place in table/ Create Frequency column/ Relative Frequency column ( frequency / n) / convert into decimal
C.
Identify Different Categories/ Tally the amount that falls into each category place in table/ Create Frequency column/ Relative Frequency column ( n/ frequency) / convert into%
D.
Identify Different Categories/ Tally the amount that falls into each category place in table/ Create Frequency column/ Relative Frequency column ( n / f) / convert into decimal
Correct Answer A. Identify Different Categories/ Tally the amount that falls into each category place in table/ Create Frequency column/ Relative Frequency column ( frequency / n) / convert into%
40.
If categorical variable is ordinal in nature the display should decrease in logical order or increase in logical order
A.
True
B.
False
Correct Answer A. True
Explanation If a categorical variable is ordinal in nature, it means that the categories have a specific order or ranking. In such cases, it is important for the display to reflect this logical order. The display should either decrease in logical order (from highest to lowest) or increase in logical order (from lowest to highest). This ensures that the data is presented in a way that accurately represents the ordinal nature of the variable.
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41.
Pie charts should be used when __________ of categories
A.
2 or more
B.
3 or more
C.
6 or more
D.
5 or fewer
E.
6 or fewer
Correct Answer D. 5 or fewer
Explanation Pie charts should be used when there are 5 or fewer categories. This is because pie charts are most effective when there are a small number of categories that can be easily compared and understood. If there are too many categories, the pie chart can become cluttered and difficult to interpret. Therefore, it is recommended to use a pie chart when there are 5 or fewer categories.
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42.
_________ Bars represent frequency counts
–Variables on horizontal axis
–Frequencies on vertical axis
A.
Hisograph
B.
Bar graph
C.
Steam and leaf plot
D.
Stacked bar graph
Correct Answer B. Bar graph
Explanation A bar graph is a type of graph that uses rectangular bars to represent the frequency counts of different categories or variables. The variables are shown on the horizontal axis, while the frequencies are shown on the vertical axis. This type of graph is commonly used to compare and display data in a visual and easy-to-understand manner.
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43.
Bar graphs Bars may be vertical or horizontal, but should touch
All must be equal width
A.
True
B.
False
Correct Answer B. False
Explanation they should not touch
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44.
Able to illustrate the natural order of data
-More appropriate for ordinal data than Pie Charts
A.
Histograph
B.
Steam and leaf polt
C.
Bar graph
Correct Answer C. Bar graph
Explanation A bar graph is able to illustrate the natural order of data because it uses bars of different lengths to represent different values or categories. The length of each bar corresponds to the quantity or frequency of the data it represents. This visual representation makes it easier to compare and understand the data. In comparison to pie charts, bar graphs are more appropriate for ordinal data because they allow for a clearer representation of the order and magnitude of the data, whereas pie charts are better suited for displaying proportions or percentages.
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45.
Pie graphs
Do not use if more than 5 categories
Order the relative frequencies in ascending or descending order.
A.
True
B.
False
Correct Answer A. True
Explanation Pie graphs are a type of data visualization that is used to represent categorical data. They are most effective when there are fewer than 5 categories. This is because pie graphs can become cluttered and difficult to interpret when there are too many categories. Therefore, it is advisable to avoid using pie graphs if there are more than 5 categories. The statement that the relative frequencies should be ordered in ascending or descending order is not relevant to the use of pie graphs and is therefore false.
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46.
Whats wrong with 3D pie chart
A.
Harder to interpert
B.
Harder to read the the scale
C.
Harder to compare fraction of the whole
D.
They look worse
Correct Answer(s) A. Harder to interpert C. Harder to compare fraction of the whole
Explanation The given answer suggests that one of the problems with 3D pie charts is that they are harder to interpret. This could be because the depth and angles of the chart can distort the perception of the sizes of the different sections, making it difficult to accurately understand the data being presented. Additionally, the answer mentions that it is harder to compare fractions of the whole in a 3D pie chart, which could be due to the added complexity and visual distractions caused by the three-dimensional elements.
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47.
If 5 or more slices are in the pie graph use a 3D pie chart
A.
True
B.
False
Correct Answer B. False
Explanation 3D isn't correct in this class
5 or fewer slices are appropriate for a pie chart
if more use table instead
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