Statistics paper

FINAL EXAM

Part 1: Interview/Oral Final (Possible Topics in BOLD) INSTRUCTIONS for Interview/Oral Exam:

• Arrive to your scheduled ZOOM interview on-time (late arrivals may not have their full 20 minutes)

• Use the ZOOM meeting ID: 909 389 3341

o https://cccconfer.zoom.us/j/9093893341 (Links to an external site.)

• Be prepared to answer questions from memory without having to read the information from notes, the use of

internet, etc

o There are concepts that require quick recall, especially the ones that have been revisited multiple

times within a lecture and/or throughout the course. For these concepts, students should be able

identify/explain/determine/perform anything about the concept/topic. The following may help guide

your thoughts:

▪ Explain what the concept/topic is about.

▪ What it does/What it's used for

▪ Talk about all aspects that make up the specific concept/topic

▪ If needed be able to describe the types of charts, graphs, and/or distributions associated

with the specific concept/topic

▪ Talk about any calculations used within the specific concept/topic

o Basically, if a student has to continually go back through notes and such then they do not know the

content enough.

• The entire goal for this the portion of the final exam is to assess your own level of understanding and ability

to demonstrate that understanding of course content.

Each question on this portion of the exam will be scored on a 4-scale rubric similar to the following:

Score of 4 Score of 3 Score of 2 Score of 1

Student demonstrates an

in-depth understanding of

the concept/topic from

memory

• Information is correct

and complete

• Explanation and/or

description is clear

• Included details

and/or examples

Student demonstrates

considerable understanding

of the concept/topic from

memory

• Information/

Explanation is correct

• Details are incomplete

or missing

• Description/

Explanation may lack

clarity and/or details

Student demonstrates

limited understanding of

the concept/topic from

memory

• Information/

Explanation are

incomplete

• Significant errors

in the details

• Examples are

incorrect

Student demonstrates

little to no

understanding of the

concept/topic

• Information is

incorrect

• Explanation

and/or details

are unclear

In order to uphold the integrity of this exam, once this portion of the exam has been completed, you

are not allowed to discuss the interview or the content within the interview with any other student.

Any student found to be sharing any information from the interview final and/or the written final will

be forwarded to the Dean of Student Services & Student Development for cheating.

Part 2: Written Final (any topic from Lectures 1 through 11)

Everyone must complete both the interview portion and written portion of the final. Anyone

who does not complete both portions of the final is the same as not taking the final which is

an automatic fail for the class.

Chapter 1:

• Sampling Techniques

• Types of Experiment Design

• Levels of Measurement

• Discrete vs Continuous

• Population vs Sample

• Qualitative vs Quantitative

• Parameter vs Statistic

• Observational vs Experiment

• Descriptive vs Inferential Statistics

Chapter 2:

• How to construct a frequency distribution

• Types of Frequency Distributions

• How to graph/Types of graphs for qualitative data

• How to graph/Types of graphs for quantitative data

• How to graph/Types of graphs for paired sets of data

• Find mean/median/mode for a population or a sample

• Identify and describe the shape of a distribution

• Entire Empirical Rule

• Find range, variance, standard deviation, and coefficient of variation for a population or sample

• Find and interpret quartiles and percentiles

• 5 Number Summary/Box and Whisker Plot

• How to interpret z-scores

Chapter 3:

• Identify simple and compound events

• Create and use Tree Diagrams to find entire sample space and probabilities of event

• Use Counting Principal

• Find probabilities of an event

• Know forms for the Complement of an event

• Independent vs Dependent events

• Find Conditional Probabilities

• Find And/Or Probabilities

• Mutually Exclusive Events

• Permutations

• Combinations

Chapter 4:

• Distinguish between discrete and continuous random variables and their types of graphs

• Construct and graph a discrete probability distribution

• Find the mean, variance, standard deviation, and expected value for a probability distribution

• Determine if a probability experiment is a Binomial Probability experiment

• Construct, graph, and describe the shape of a Binomial Probability Experiment.

• Find Binomial Probabilities using EXCEL

• Identify any random variables that would be considered unsual

• Find the mean, variance, and standard deviation for a Binomial Distribution

• Distinguish between Binomial and Poisson Distributions

• Identify and find probabilities of a Poisson Distribution

Chapter 5:

• Know difference between Standard Normal Distribution and Normal Distributions

• Find areas/probabilities of Standard Normal Distribution and Normal Distributions

• Find z-scores for Standard Normal Distribution and Normal Distributions

• Find a given data value from a given z-score

• Know when and how to use Central Limit Theorem to find the probability of a sample mean

• Determine when a normal distribution can be used to approximate a binomial distribution

Chapter 6:

• Know the differences between all four of the confidence intervals

• Be able to construct and interpret all four of the confidence intervals

• Be able to find the point estimate and Margin of Error for population proportions and means

• Find the minimum sample size needed when estimating a population proportion or mean (𝜎 𝑘𝑛𝑜𝑤𝑛)

• Know which populations use Standard normal distribution (z-scores), student-t distribution (t-scores), and chi-square Distributions

(𝝌𝟐-scores).

Chapter 7:

• Explain how to identify, determine, and write the null and alternate hypothesis

• Be able to identify and determine Type I and Type II errors

• How to write the claim and conclusion of a hypothesis test

• Identify and determine the tail of a hypothesis test

• Know requirements for each of the hypothesis tests

• Identify and determine the type of hypothesis test is to be performed including its distribution and type of

scores (z, t, 𝝌𝟐)

• Be able to calculate and interpret critical values and p-values for all hypothesis tests

• Identify the rejection/fail to reject regions of a specific hypothesis test and be able to state why we reject or fail to reject the null

• Perform a complete hypothesis test for each distribution

Chapter 8:

• Know the requirements for a two sample difference between two population means hypothesis test

• Determine, identify, and perform a two sample difference between two population means hypothesis test

• Explain what the difference between the two means for this test

• Be able to calculate the p-value and critical values a two sample difference between two population means hypothesis test

• Perform a complete hypothesis test for the difference between two population means

Chapter 9:

• Identify and determine the explanatory and response variables

• Construct a scatter plot

• Find the correlation coefficient of the sample and the critical values

• Find the regression equations

• Identify and determine the type of correlation a set of data has from the graph or the correlation coefficient

• Explain how to determine whether a set of data has a linear correlation or not

• Explain the best predicted value for a regression equation and its sample statistics

• Explain 𝑹𝟐

• Perform a complete linear regression hypothesis test

Chapter 10:

• Describe the distributions for the goodness of fit and ANOVA tests

• Explain, identify, and determine when to use a goodness of fit test and/or an ANOVA test

• Compare and Contrast the

goodness of fit and ANOVA test

• Know requirements and determine the tails for the goodness of fit and ANOVA hypothesis test

• Perform a complete goodness of fit and ANOVA hypothesis test

• Explain how to determine which expected frequency equation is needed within the goodness of fit test

Chapter 11:

• Describe the difference between parametric and non-parametric statistics

• Know requirements for the non-parametric test

• Explain how this test is different from all other hypothesis tests

• Explain the differences in the test when n > 25 and when n < 25

• Perform a complete non- parametric hypothesis test