Statistics Exam 1 Review

• Exam 1 includes 40 questions to be answered in 50 minutes.
• The exam is in person and on paper; a scantron will be provided.
• Mutually exclusive events should be understood with examples.

Branches of Statistics

• The two branches of statistics are: descriptive and inferential.

Independent Events Notation

• Notation for two independent events should be understood.

Z-Score

• A Z-score includes characteristics, formula, and calculation with given numbers.

Population vs Sample

• Population definition including how a sample differs from a population should be understood.
• Examples of population and its corresponding sample should be practiced.

Variable Data

• Examples differentiating quantitative vs. qualitative variables/data should be understood.
• Examples differentiating descriptive vs. inferential data should be understood.

Data Subset

• Reasons for subsetting data should be understood.

Horizontal Bar Chart

• The process of creating a horizontal bar chart should be understood.
• The appropriate graphical tool should be used to display the relative frequency of a numerical variable.

Frequency

• Understanding, finding, and defining frequency is key.
• The ability to find relative frequency from a frequency table should be understood.
• The process of finding relative frequency should be understood.
• The difference between relative frequency and percent frequency should be understood.

Budget Allocation

• Calculation of spending given budget percentages is relevant.
• For instance, spending 35% of a weekly food budget with a $200 monthly budget requires calculation.

Observation Proportion

• Determining the proportion of observations within a specified range requires calculation.
• For example, determining the proportion of observations at least 18 but less than 24.

Statistics and Outliers

• Recognizing the statistic most influenced by outliers is important.

Probability Calculation

• Probability calculations involving customer preferences need to be understood.
• For instance, calculation of randomly selected customer's beer order probability at a local bar.

Camera Brand Probability problem

• Determining probability from a table using conditional probability.
• Given that a camera purchase was at Amazon.com, calculate the probability it was a Canon brand.

Data Types

• Understanding types of data and knowing the difference btwn time series data and cross-sectional data.

Statistics Definition

• Definition of a statistic should be known.

Mean, Median, and Mode

• Understanding mean, median, and mode, including which is most influenced by outliers, is required.

Frequency Case Study

• Use a table to take a statistic like a percent or relative frequency
• Find the number given the population size by remembering the relative frequency case study.

Empirical Rule

• The empirical rule should be understood.

Dispersion Statistics

• Knowing the most common statistics to show dispersion is necessary.

Variance

• Understanding variance, what it shows, and its relation to standard deviation is important.

Covariance

• Definition of covariance.

Collectively Exhaustive Event

• How an event can be collectively exhaustive should be understood.

Union in Probability

• Definition of a union in probability and recognize the notation.

Intersection in Probability

• Understanding of the intersection of 2 events in probability notation.
• The intersection of events A = {The Porch, Louie's, The Library, O'Connell's} and B = { The Library, O'Connell's, Logies, Volare} is {The Library, O'Connell's}.
• The union of events A = {The Porch, Louie's, The Library, O'Connell's} and B = { The Library, O'Connell's, Logies, Volare} is {The Porch, Louie's, The Library, O'Connell's, Logies, Volare}.

Probability Summation

• All probabilities must add up to 1.

Event Outcomes

• When an event has one outcome, it is an elementary event.

Sample Space

• Understanding of sample space should be there.
• Determine the sample space for letter grades in a class.

Complement of A

• Understanding of the complement of A given sample space S is required.

Correlation Coefficient

• Correlation coefficient formula and calculation should be understood.

Standard Deviation

• Deriving standard deviation from variance should be understood.

Exam Score Probability

• Determining exam score probability given average and standard deviation.
• Knowing if the average on exam 1 is an 85 with a standard deviation of 1.5, what is the probability you score less than 75.
• What is the probability you score greater than a 90?