Descriptive Statistics Concepts 2

<p>Female (C)</p> Signup and view all the answers

<p>18-21 (B)</p> Signup and view all the answers

<p>Medical doctor (A)</p> Signup and view all the answers

<p>Three (A)</p> Signup and view all the answers

<p>Small sample size (D)</p> Signup and view all the answers

<p>55.24% (A)</p> Signup and view all the answers

<p>10 (B)</p> Signup and view all the answers

<p>To provide a convenient whole number (D)</p> Signup and view all the answers

<p>Each case can belong to only one interval. (D)</p> Signup and view all the answers

<p>Total cases (D)</p> Signup and view all the answers

<p>Overlapping intervals (A)</p> Signup and view all the answers

<p>35–37 hours (A)</p> Signup and view all the answers

<p>44.76% (D)</p> Signup and view all the answers

<p>Histograms use real limits whereas bar charts use stated limits. (D)</p> Signup and view all the answers

<p>Label each interval with its corresponding frequency. (D)</p> Signup and view all the answers

<p>Continuous interval-ratio level variables. (B)</p> Signup and view all the answers

<p>The real limits of the intervals. (A)</p> Signup and view all the answers

<p>Both axes need titles that reflect the data dimensions. (D)</p> Signup and view all the answers

<p>They present data in a visually dramatic manner. (D)</p> Signup and view all the answers

<p>Discrete variables at any level of measurement. (A)</p> Signup and view all the answers

<p>Histograms (D)</p> Signup and view all the answers

<p>Ensuring a clear division of segments proportional to percentages. (D)</p> Signup and view all the answers

<p>Using advanced computer software. (D)</p> Signup and view all the answers

<p>Labels that clearly identify each category. (C)</p> Signup and view all the answers

<p>360° (D)</p> Signup and view all the answers

<p>Line Graph (D)</p> Signup and view all the answers

<p>Using real limits (B)</p> Signup and view all the answers

<p>Add 0.5 to upper limits and subtract 0.5 from lower limits (B)</p> Signup and view all the answers

<p>It shows distributions as continuous with overlap (A)</p> Signup and view all the answers

<p>19.5–21.5 (A)</p> Signup and view all the answers

<p>23.5 (A)</p> Signup and view all the answers

<p>Real limits eliminate the gaps present in stated limits. (D)</p> Signup and view all the answers

<p>They encompass all potential scores within two stated limits. (D)</p> Signup and view all the answers

<p>Because scores can only be whole numbers. (D)</p> Signup and view all the answers

<p>It is the percentage of cases in the interval plus the percentage of cases in the lower interval. (B)</p> Signup and view all the answers

<p>To maximize clarity and ease of comprehension. (D)</p> Signup and view all the answers

<p>Add an open-ended interval to accommodate those scores. (C)</p> Signup and view all the answers

<p>It does not specify the exact scores included in the interval. (D)</p> Signup and view all the answers

<p>You must add new intervals for the high scores. (B)</p> Signup and view all the answers

<p>The exact scores that fall within those intervals. (C)</p> Signup and view all the answers

<p>They should clearly indicate changes in data density. (C)</p> Signup and view all the answers

<p>Confusion over the actual data distribution. (B)</p> Signup and view all the answers

<p>To test hypotheses and draw conclusions about a population. (C)</p> Signup and view all the answers

<p>Descriptive statistics are based on complete datasets, while inferential statistics use samples. (B)</p> Signup and view all the answers

<p>Studying the prevalence of a disease across different regions. (A)</p> Signup and view all the answers

<p>It provides a clearer overview of patterns and trends than numerical summaries. (C)</p> Signup and view all the answers

<p>They can obscure important details if not carefully examined. (D)</p> Signup and view all the answers

<p>To summarize and accurately describe main features of a data set. (C)</p> Signup and view all the answers

<p>Drawing conclusions about a population from a sample. (B)</p> Signup and view all the answers

<p>Mode is unaffected by extreme values. (C)</p> Signup and view all the answers

<p>Descriptive statistics provide a summary of data, while inferential statistics aim to generalize findings. (A)</p> Signup and view all the answers

<p>Variance (C)</p> Signup and view all the answers

<p>Categorical data. (B)</p> Signup and view all the answers

<p>They assess the symmetry or asymmetry of a distribution. (B)</p> Signup and view all the answers

<p>It indicates the degree of asymmetry in a distribution. (D)</p> Signup and view all the answers

A table that shows the number of times each value occurs in a set of data.

The process of collecting, analyzing, and interpreting data to draw conclusions.

A survey used to gather feedback on a patient's experience.

Information collected on students' visits to university health services.

Measurable characteristics of the data, such as gender, type of health professional, satisfaction levels, and age.

Categories of healthcare providers like medical doctors, counsellors, and others.

A rating of how satisfied a student is with the health service.

Data that describes the sample/population. This does not include calculations like averages. Here it describes the students' experience with the health center.

Used to treat a variable as continuous instead of discrete, eliminating gaps between intervals.

The apparent boundaries or intervals of data, creating non-overlapping units.

A variable that can take on any value within a given range.

Determine real limits by adding half the interval width to the upper stated limit and subtracting it from the lower stated limit.

The difference between two stated limits. This difference is critical for calculating real limits.

A bar graph used to visually represent frequency distributions. Continuous variables are useful here.

A variable that can only take on specific values and not intermediate ones.

Intervals with shared values are overlapping.

A frequency distribution where the size of each interval is different. This is typically used when some scores are extremely high or low.

An interval in a frequency distribution that includes all scores above or below a specified value. Used to compactly represent very high or low scores without listing every single empty interval.

Unequal intervals are useful when a few scores are extremely high or low, making it inefficient to use equal intervals. Open-ended intervals are used to represent these extreme scores in a compact way.

While open-ended intervals save space and simplify data presentation, they lose the precision of knowing the exact scores within that interval.

The percentage of cases in an interval combined with the percentages of cases in all lower intervals. Helps visualize the proportion of scores that fall below a certain point.

The interval with the highest scores always has a cumulative percentage of 100%. This indicates all scores fall within or below that interval.

To calculate cumulative percentage, add the percentage of cases in an interval to the percentage of cases in the lower intervals. Continue this process until you reach the highest interval.

Using equal intervals in frequency distributions generally improves clarity and ease of comprehension. It makes it easier to analyze and compare data trends.

The width of each interval in a frequency distribution. It is calculated by dividing the range of scores by the number of intervals.

The difference between the highest and lowest scores in a dataset. It tells you the spread of the data.

The number of categories or groups you divide your data into when creating a frequency distribution. This is the number of rows in your frequency distribution.

The number of times a specific value or interval occurs in a dataset.

Histograms are particularly useful for displaying continuous variables, as they allow us to see the distribution of the data, identify patterns, and understand trends in a visually appealing way.

Building a histogram involves mapping real limits of intervals to the horizontal axis, frequencies to the vertical, and bars with heights representing frequency counts and widths corresponding to the real interval limits.

A circular graph divided into slices representing proportions of a whole. Each slice's size reflects the percentage of the variable's category.

A graph with rectangular bars representing categories of a variable, where the height of each bar shows the frequency or proportion of that category.

A line graph that connects points representing the frequencies of each data value, showing the distribution of data.

A graph representing data distribution with a box showing the middle 50% of the data, lines extending to the minimum and maximum values, and a line indicating the median.

Charts and graphs are more visually appealing and easier to understand than raw data. They highlight patterns and trends in data.

The average value of a dataset, calculated by summing all values and dividing by the total number of values.

The middle value of a sorted dataset, dividing it into two equal halves.

The most frequent value occurring in a dataset.

The difference between the highest and lowest values in a dataset.

The square root of the variance, representing the average distance of data points from the mean.

A measure of the asymmetry of a distribution, indicating if it's skewed to the left or right.

A measure of the 'peakedness' of a distribution, indicating if it's more or less peaked than a normal distribution.

Descriptive statistics summarize data, inferential statistics test hypotheses and draw conclusions about populations based on samples.

Descriptive stats are used in various fields, including business, healthcare, education, and social sciences to analyze and summarize data.

Charts and graphs, like histograms, box plots, and scatter plots, are vital for understanding data patterns and trends.

Summary statistics can hide crucial details, outliers can skew results, and choosing appropriate measures is important.