Biostatistics Trivia Quiz Part 1

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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).

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).

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Variables are characteristics recorded about each individual. The name of the variable should identify what has been measured.

3D isn't correct in this class
5 or fewer slices are appropriate for a pie chart
if more use table instead

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.

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.

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.

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".

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.

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.

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.

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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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.

they should not touch

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.