Lesson-1.pdf

Prelim Topics Lesson 1: Introduction to Statistics (10 hours) - Importance of Statistics - What is Statistics - Variables and Scales of Measurement - Experimental and Non-Experimental Research STATISTICAL BIOLOGY INTRODUCTION TO STATISTIC...

Prelim Topics Lesson 1: Introduction to Statistics (10 hours) - Importance of Statistics - What is Statistics - Variables and Scales of Measurement - Experimental and Non-Experimental Research STATISTICAL BIOLOGY INTRODUCTION TO STATISTICS  Activity 1 Why is Statistics important? Presentation - 10 points Completeness - 10 points Correctness - 10 points Total - 30 points INTRODUCTION TO STATISTICS IMPORTANCE OF STATISTICS IMPORTANCE OF STATISTICS IMPORTANCE OF STATISTICS IMPORTANCE OF STATISTICS IMPORTANCE OF STATISTICS IMPORTANCE OF STATISTICS WHAT IS STATISTICS? Basically, statistics deals with data. Data are collected, organized, presented, analyzed and interpreted for a sound decision making. WHAT IS STATISTICS? WHAT IS STATISTICS?  infer or generalize or describe data conclude from incomplete information BRANCHES OF STATISTICS  Methods of organizing, displaying or describing data 1. Tables 2. Graphs 3. Summary Measures describe data BRANCHES OF STATISTICS BRANCHES OF STATISTICS  is concerned with reaching conclusions from incomplete information - that is, generalizing from the specific. It also uses information obtained from a sample to say something about the entire population. infer or generalize or conclude from incomplete information BRANCHES OF STATISTICS Determine whether the statements describe inferential statistics or descriptive statistics. 1. The most common age of the students in a statistics class is 18 years old. 2. There is a relationship between exam scores and number of hours spent in studying. 3. From the past figures, it is predicted that 5% of the COVID-infected patients will be intubated. 4. According to various studies, it takes around 3 months to 1 year to fully move on from a heartbreak. 5. Male students have 20% higher chance to drop out, than female students. BRANCHES OF STATISTICS  2 points each ACTIVITY 2 Score + 5 Determine whether the statements describe inferential statistics or descriptive statistics. 1. The most common age of the students in a statistics class is 18 years old. descriptive 2. There is a relationship between exam scores and number of hours spent in studying. inferential 3. From the past figures, it is predicted that 5% of the COVID-infected patients will be intubated. inferential 4. According to various studies, it takes around 3 months to 1 year to fully move on from a heartbreak. descriptive 5. Male students have 20% higher chance to drop out, than female students. descriptive BRANCHES OF STATISTICS  Laboratory Activity 1 “My Best Decision” Directions: Write an essay of at most 4 paragraphs discussing the best decision you’ve made in your life. Here are the questions that will guide your write up: 1. What is the best decision you’ve made in your life? 2. Why do you consider this decision as your best? 3. Was this decision based on data? Why or why not? IMPORTANCE OF STATISTICS IMPORTANCE OF STATISTICS STATISTICAL BIOLOGY  Most Loving Gracious and Heavenly Father, I come to your presence this day. Father God, I want to walk with You. Help me, Lord, to crave a life that is led by You. Today, please fill me with your Spirit’s wisdom, power, and strength. Lord, give me the courage to be still and trust You. Teach me to listen to Your Spirit, and show me how to obey You faithfully and follow you boldly. In Jesus’ name, Amen. STATISTICAL BIOLOGY  2 points each ACTIVITY 2 Score + 5 Determine whether the statements describe inferential statistics or descriptive statistics. 1. The most common age of the students in a statistics class is 18 years old. descriptive 2. There is a relationship between exam scores and number of hours spent in studying. inferential 3. From the past figures, it is predicted that 5% of the COVID-infected patients will be intubated. inferential 4. According to various studies, it takes around 3 months to 1 year to fully move on from a heartbreak. descriptive 5. Male students have 20% higher chance to drop out, than female students. descriptive BRANCHES OF STATISTICS  Laboratory Activity 1 “My Best Decision” Directions: Write an essay of at most 4 paragraphs discussing the best decision you’ve made in your life. Here are the questions that will guide your write up: 1. What is the best decision you’ve made in your life? 2. Why do you consider this decision as your best? 3. Was this decision based on data? Why or why not? IMPORTANCE OF STATISTICS IMPORTANCE OF STATISTICS IMPORTANCE OF STATISTICS IMPORTANCE OF STATISTICS uses information obtained from a sample to say something about the entire population POPULATION VERSUS SAMPLE  POPULATION SAMPLE The population consists of all The sample is a portion or a subset elements, individuals, items, or of the population. objects – whose characteristics are being studied. The measurable quality is called a The measurable quality is called a parameter. statistic. Reports are a true representation Reports have a margin of error of opinion. and confidence interval. POPULATION VERSUS SAMPLE Example Which of the following set of data is a population? A sample? 1. The age of all SUNN students for 1st semester, AY 2024 – 2025. 2. The brand of mobile phone of every fifth student who enters the SUNN Library. 3. The monthly allowance of all junior BS Biology students. 4. The number of pets in all households of Negros Occidental. POPULATION VERSUS SAMPLE  POPULATION SAMPLE The population consists of all The sample is a portion or a subset elements, individuals, items, or of the population. objects – whose characteristics are being studied. The measurable quality is called a The measurable quality is called a parameter. statistic. Reports are a true representation Reports have a margin of error of opinion. and confidence interval. POPULATION VERSUS SAMPLE Example Determine whether the numerical value is a parameter or a statistic. 1. The average annual salary of 35 out of 1200 BPO employees in Bacolod City is Php 300, 000.00. 2. In a recent year, the interest category for 12% of all new magazines was sports. 3. In a recent survey of 1000 college students in the Philippines, 47% said they prefer in person classes. 4. This year, the average math grade of all senior high school graduates in the Philippines is 85. POPULATION VERSUS SAMPLE  ACTIVITY 3 Determine whether the statements describe a population or a sample. 1. A group of 25 mice selected for erythrocyte count 2. Leucocyte numbers of every Filipino male of age 20 3. DNA content of all hamster sperm cells in existence 4. Heartbeat frequencies of chosen broken hearted teens 5. Platelet count of 100 outpatients of a government hospitals in the Philippines POPULATION VERSUS SAMPLE  ACTIVITY 4 Determine whether the numerical value is a parameter or a statistic. 1. In a national survey on substance abuse, 10% of selected respondents aged 12 to 17 reported using illicit drugs within the past month. 2. Ty Cobb is one of major league baseball’s greatest hitters of all time, with a career batting average of 0.366. 3. A study of all adults in public rest rooms (in Negros Occidental, Negros Oriental, Iloilo, and Guimaras) found that 23% did not wash their hands before exiting. 4. Interview of 100 students 18 years of age or younger, conducted nationwide, found that 44% could state the minimum age required for the office of Philippine president. PARAMETER VERSUS STATISTIC  A variable is a characteristic under study that assumes different values for different elements. Examples: Diastolic blood pressure heart rate height of adult males weight of pre-school children stage of bladder cancer patients TYPES VARIABLES Variables be categorized as either quantitative (numerical) or qualitative (categorical). Examples: Diastolic blood pressure heart rate height of adult males weight of pre-school children stage of bladder cancer patients TYPES OF VARIABLES Qualitative (categorical) Quantitative (numerical) variables variables are variables that can be are variables that assume grouped by specific meaningful numerical categories. values. Examples: hair color and Examples: height of BSBio eye color students and number of COVID cases. TYPES OF VARIABLES Quantitative (numerical) variables can either be discrete or continuous. A discrete variable assumes a countable number of values. It answers the question 'how many?’ A continuous variable is characterized by uncountable values within an interval. It answers the question 'how much?'. TYPES OF VARIABLES  ACTIVITY 5 Determine whether the given variables are qualitative or quantitative the variable is quantitative, specify whether it is discrete or continuous. 1. The number of pregnancies 2. Degree of pain 3. Students score in a particular quiz in Biostatistics 4. Ethnic group of patients 5. Body Mass Index of outpatients in a government hospital 6. The number of bacteria colonies on a plate TYPES OF VARIABLES STATISTICAL BIOLOGY  Most Loving Gracious and Heavenly Father, thank you because of your Son Jesus, sin have no control over my life. But because the world isn’t fully restored yet, I still find myself tempted. Father God, Your Word says that You will provide a way through temptation. Thank You! Please help me see a way out of temptation and the courage to say “no” to things that could harm me. I want to faithfully follow you at all times. In Jesus’ name, Amen. MATHEMATICS IN THE MODERN WORLD Functions of variables are important if the investigation is about cause & effect. Distinctions: Independent Variable Dependent Variable FUNCTIONS OF VARIABLES Independent Variables Dependent Variables - the variable that - The variable that is researcher manipulates (a affected (the effect or program, a treatment or a outcome) by the cause) in order to observe independent variable the effect on a dependent variable - also known as outcome variable - also known as experimental or predictor variable TYPES OF VARIABLES Example 1. Investigating how the growth of milkweed bugs is affected by their food supply. 2. Effect of grapefruit juice on cyclosporine and prednisone metabolism in transplant patients. 3. Influence of smoking cessation on weight in adults. TYPES OF VARIABLES the aim is to manipulate an independent variable(s) and then examine the effect that this change has on a dependent variable(s). Since it is possible to manipulate the independent variable(s), experimental research has the advantage of enabling a researcher to identify a cause and effect between variables EXPERIMENTAL VS. NON-EXPERIMENTAL RESEARCH  the researcher does not manipulate the independent variable(s). This is not to say that it is impossible to do so, but it will either be impractical or unethical to do so EXPERIMENTAL VS. NON-EXPERIMENTAL RESEARCH ACTIVITY 6 30 points Group Activity SCALES OF MEASUREMENT VARIABLES AND SCALES OF MEASUREMENT SCALES OF MEASUREMENT Temperature Final Grade Hair color Severity of Disease Age Blood Pressure (Low, High) Weight Socio-economic Status Time until death Mobile Number Student ID Number Account Number Birth Order Height Place of Residence SCALES OF MEASUREMENT NOMINAL ORDINAL INTERVAL RATIO Hair Color Birth Order Temperature Age Student ID Year Level Time Weight Number Course Latin Honors Final Grade Height Mobile Performance Number Rating Account Number SCALES OF MEASUREMENT Nominal data > can either be numeric or non-numeric > uses labels or names to identify the attribute of the element > numbers do not have values > numbers indicate categories for purely classification or identification purposes SCALES OF MEASUREMENT Nominal data Student ID number Mobile number Course number (e.g. GE 101, GE 102, PASC4 and etc.) SCALES OF MEASUREMENT Ordinal data > the data exhibits the properties of nominal data and the order or rank of the data is meaningful > represents an ordered series of relationships > Examples: Birth order, Honors, Order of finishing a race, Difficulty SCALES OF MEASUREMENT Interval data > can be categorized and ranked, and differences between values are meaningful > has no absolute zero > Example: Temperature SCALES OF MEASUREMENT Ratio data > the strongest level of measurement > data have all the properties of interval data and the ratio of two values are meaningful > has a true or absolute zero point > Example: Weight, Age, Distance SCALES OF MEASUREMENT