Statistics and Computer Applications in Natural Sciences (ENV-200 and 200L)
Fall 2020
Instructors: Dr. Hongbing Sun
Periods: Synchronous Zoom Lecture- Tuesday
& Thursday, 9:45-11:15 in Rm STC 334.
Synchronous Zoom Laboratory –Wed (1:10- 4:10)
Students are required to have a computer and connection to
internet. Preferably have Microsoft office on your computer as well.
My office is located in Science
Building, room 323C. However, office visit this semester is expected to be all
virtual. You can email me and I can schedule a zoom virtual meeting with you.
The times I am definitely AVAILABLE (office hrs) are:
Tuesday, Thursday morning 10-11:00 AM, Wed 10-11 AM. Other times, I might be
available and you need to schedule.
Objectives: Student will learn variables, basic probability, central tendency, variability, graphical representation, scales, sampling procedures, hypothesis testing, and statistical interpretation of biological, environmental, marine, and geological data. This course will address the departmental assessment goals of enabling students to demonstrate knowledge of interpretation of spatial and temporal graphical data in the form of various graphs and maps to either support or reject scientific hypotheses.
Text: Elementary Statistics, Tenth Edition by Allan
Bluman.2018
Reference: Biostatistical Analysis (5th edition) by J. H. Zar, 2010.
Evaluations: Three lecture exams: 51% of the total, each exam: 17%. Homework & In-class exercises: 15%. Laboratory Exercises: 35%. Total points will be 101 points.
My grading policy is as follows: A range >90, B range 80-89, C range 70-79, D range 60-69, F range <60. "Borderline" cases will be judged individually, based on grade improvement, demonstrated effort and class participation, etc.
Zoom Attendance Is Required. Regular attendance makes a big difference in the final grade received. The material in this class is cumulative. If you miss a day, you may find that you are lost during the next lecture. Four unexcused absences will result in a drop of your final score by 4 points. Excessive absences will result in more deducted points from your total score (or you being dropped from the course). Excuses for absence will be granted for approved athletic participation, approved field trips, a certified serious illness, death in the immediate family and military examinations. Absence from class, no matter what the reason, does not grant the student a chance to make up the in-class exercises or a quiz. Instructors permission for withdrawal will be given only for exceptional circumstances. Make-up exams are generally not given and a grade of "F" is given for any regularly scheduled exam that is missed.
Note: In order to be excused for an absence, you must have documentation to validate your excuses. For example, if you are sick, you need a doctor’s note to show me. If your car broke down, you need a slip from the towing company or your mechanics. Also it is my experience that self-motivated students tend to do better in this course. If you usually leave things to the last minute, it may be difficult for you to keep your grades at an acceptable level. If your math skills are a bit rusty or you are a bit fearful of math in general, I suggest you pick up additional reference books such as Basic Statistics or Statistics for Dummies from the library or book stores.
Cheating: Academic integrity is highly valued at Rider. Students caught cheating during an examination will be removed from the class and given a "zero" for that test.
Class schedules are tentative, may change during the semester
Dates: Lecture/Laboratory Topic Reference Chapter
Class
schedules are tentative, may change during the semester
Dates: Lecture/Laboratory
Topic
Reference
Chapter
Sept. 1 Basic
Data and Types of Graphs
NO
LAB
3
Types of data, stats,sampling procedures Chpt1
8 Scales of
Geological/Biological Data
Lab - Graphical Representations of Data
10 Frequency
distributions, types of graph Chpt. 2
15
Population
Estimators; Central Tendency
Lab - Ternary Diagrams
22 Measures
of Dispersion and Variation chapter
3
24 normal
distribution Chapter
6.
Lab - Descriptive Statistics; normal distribution
29 Community
Estimators/Diversity Indices
Handout
Oct 1
Exam (Types of Graphs
–Community Estimators)
Lab - t-Test; Pairing Design Test; Wilcoxon Test; Median Test
6
Hypothesis
Formation & Testing, normal distribution Chpts 7
8 Tests
for Central Tendency
Chapter
8
Lab - Kolmogorov-Smirnov Test; Mann-Whitney U Test
13
Tests for Central Tendency- t-z, test
Chapter
9
15
Poisson Distributions & Randomness
Lab - Goodness of Fit Test; Runs Test; Binomial Test
20
Circular Distributions of Data Handout-chp25.
22 Tests
of Orientational Data
Lab - Rose Diagrams & Tests of Orientational Data
Oct 27 Spatial
data
29 Spatial
data, Tests of Spatially Distributed Data Notes
Lab - Nearest Neighbor Test & Variance/Mean Ratio Test
Nov 3
Exam (Tests of Central Tendency to
Spatially Distributed Data)
5
Cluster
Analysis Notes
Lab
- Cluster Analysis
10 Sequential
Events, Homogeneity
of Variance Notes
13 Analysis of
Variance (One way)
Chpt12
Analysis
of Variance (Two way)
Lab - Bartlet's Test & F-Test
17 Bivariate
Data-Correlation
Chpt 10
Nov. 19. Correlation
Test Chpt10
24 Correlation
Tests
Nov. 25-28. NO CLASS- THANKSGIVING RECESS
NO Lab- THANKSGIVING RECESS
Dec 1 Regression
Analysis
Lab
- One Way and Two ANOVA; Tukey & Neuman-Keuls
Correlation Tests & Regression Analysis
Dec 3 Multivariate
regression. Homogeneity of variance
to
regression analysis. MANOVA and Wrap up
Final
Exam: Monday, Dec 8, 10:30am-12:30pm.
To Geology Department Homepage To Dr. Sun's Homepage|
E-mail Dr. Sun: hsun@rider.edu
Last updated 8/26/2020