Module 1 Introduction to Statistics PSY 002 PDF

Module 1 Introduction to Statistics PSY 002...

Module 1 Introduction to Statistics PSY 002 PSYCHOLOGICAL STATISTICS This is your first module! This module is for synchronous learning and will last for two weeks COLLEGE OF ARTS AND SCIENCES C GINA T. MONTALLA Instructor Gina T. Montalla SMMC [email protected] 09176147214 August 29, 2023 Date Initiated September 9, 2023 San Mateo Municipal College Date of Completion Gen. Luna St. Guitnang Bayan I, San Mateo, Rizal Tel. No. (02) 997-9070 www.smmc.edu.ph  SAN MATEO MUNICIPAL COLLEGE (PSY 002) PSYCHOLOGICAL STATISTICS General Luna St., Guitnangbayan I, San Mateo, Rizal MRS. GINA T. MONTALLA Tel. No. (02) 997-9070 MODULE 1: MODULE SCHEDULE: Synchronous Meeting: 5hrs. / week LEARNING OBJECTIVES: After completing this module, you should be able to: 1. enumerate the four methods of studying truth; 2. define and contrast important statistical concepts such as observational versus experimental research; descriptive versus inferential statistics; 3. define basic statistical concepts: population, sample, variable, statistic, and parameter; 4. explain why random sampling is important; 5. differentiate measurement scales such as nominal, ordinal, interval and ratio; and 6. differentiate and give examples of continuous and discrete variables INPUT INFORMATION TOPICS: Statistics, Science and Observation Population and Samples Data Structures, Research Methods and Statistics Statistical Notations Random Sampling Slovin’s Formula Probability and Non-Probability Sampling Techniques Scale of Measurements STATISTICS Refers to a set of mathematical procedures for organizing, summarizing, and interpreting information. Consists of facts and figures such as average income, crime rate, birth rate, average snowfall, and so on. The branch of mathematics which deals with the collection, organization, and interpretation of data 1|Page PSYCHOLOGY SOCIETY  SAN MATEO MUNICIPAL COLLEGE (PSY 002) PSYCHOLOGICAL STATISTICS General Luna St., Guitnangbayan I, San Mateo, Rizal MRS. GINA T. MONTALLA Tel. No. (02) 997-9070 A scientific body of knowledge that deals with the collection, organization, presentation, analysis, and interpretation of data. ❖ Collection – refers to the gathering of information or data ❖ Organization or presentation – involves summarizing data or information in textual, graphical or tabular forms ❖ Analysis – involves describing the data by using statistical methods and procedures ❖ Interpretation – refers to the process of making conclusions based on the analyzed data General purpose of Statistics in research ❖ Statistics are used to organize and summarize the information so that the researcher can see what happened to the research study and can communicate the result to others. ❖ Statistics help the researcher to answer the general questions that initiated the research by determining exactly what conclusion are justified based on the result that were obtained. POPULATION AND SAMPLES Population ❖ The set of all the individuals of interest in a particular study. ❖ The totality of the elements from which data under consideration shall be obtained ❖ Refers to a large collection of objects, persons, places, or things. ❖ It is usually denoted or represented by N Sample ❖ It is a set of individual selected from a population, usually intended to represent the population in a research study. ❖ A representative portion of the population taken for a study. ❖ A small portion or part of the population. ❖ It could also be defined as a subgroup, subset, or representative of a population. ❖ It is usually denoted or represented by n The relationship between a population and a sample 2|Page PSYCHOLOGY SOCIETY  SAN MATEO MUNICIPAL COLLEGE (PSY 002) PSYCHOLOGICAL STATISTICS General Luna St., Guitnangbayan I, San Mateo, Rizal MRS. GINA T. MONTALLA Tel. No. (02) 997-9070 PARAMETER AND STATISTIC Parameter ❖ Parameter is usually a numerical value that describes a population. ❖ It is any numerical or nominal characteristic of the population. It is a value or measurement obtained from the population. Statistic ❖ Statistic is usually a numerical value that describes a sample. ❖ Statistic is an estimate of parameter. It is any value or measurement obtained from a sample. VARIABLES AND DATA Variables ❖ A characteristic or condition that changes or has different values for different individuals. ❖ A characteristic or property of the population or sample which makes the members different from each other. ❖ Examples: age, gender, grades, type of family, job satisfaction, gender, height, weight, personality, temperature, time of the day, size of the room, etc. ❖ Classification of variables ▪ Discrete Variables - consists of separate, indivisible categories. No values can exist between two neighboring categories. Examples: Gender, Nationality, Occupation, Number of students in a classroom, etc. ▪ Continuous Variables - there are an infinite number of possible values that fall between any two observed values. A continuous variable is divisible into an infinite number of fractional parts. Ex. Weight, Height, Average grade, income, age, etc. Data (Datum) ❖ Measurements or observations. ❖ Facts or set of information or observation under study. More specifically, data are gathered by the researcher from a population or from a sample. ❖ Classification of Data ▪ Metric Data – data obtained by measurement. Examples: height, weight, age, monthly income, performance rating, scores in a test, grades, length of teaching experience, etc. ▪ Examples of this kind of data are the following: height of first year students in your school weight of all thirteen year-old students in your school age of fathers in your neighborhood monthly income of families in your barangay performance ratings of the teachers in one elementary school in your municipality scores of the Grade VI pupils in a school in the assessment test given by the government scores of the fourth year students in your school in a government —made achievement test grades in mathematics of the third year students in your school scores in the entrance test of the incoming freshmen in your school 3|Page PSYCHOLOGY SOCIETY  SAN MATEO MUNICIPAL COLLEGE (PSY 002) PSYCHOLOGICAL STATISTICS General Luna St., Guitnangbayan I, San Mateo, Rizal MRS. GINA T. MONTALLA Tel. No. (02) 997-9070 length of teaching experience of the teachers in a public high school in your place ▪ Enumeration Data – data obtained by counting. Examples: number of students in a classroom, number of households in a barangay, number of working students, etc. ▪ Sources of enumeration data are likewise numerous. Here are some examples. how many professionals in your barangay are single and married how many physically disabled individuals study in your school how many students belong to extended families how many students have separated parents how many teachers in your school have excellent performance ratings how many students have either or both parents working abroad how many students have computers at home how many families in your barangay are renting a house how many pupils in a public elementary school in your barangay have learning difficulties how many working students are there among the high school students in your school ▪ Categorical Data – data which can be classified into groups or categories of responses. Examples: attitudes, perceptions, personality traits, study habits, socio-economic status, level of stress, level of implementation ▪ Data of this kind hardly come from They are described terms of criteria. Some examples are as follows: attitudes of workers in a company towards their superiors perceptions of third year students about their teachers personality traits of teachers in your school study habits of the students in your school level of involvement of families in your barangay in community development socio-economic status of families in your neighborhood level of reading ability of Grade IV pupils in a private school in your municipality morale of the workers in a factory in your locality level of stress suffered by takers of government examinations level of implementation of quality management in hospitals in your municipality Data collection requires that we make measurements of our observations. Statistics deals mostly with measurements. Measurement involves assigning individuals or events to categories. The categories can simply be names such as male/female or employed/unemployed, or they can be numerical values such as 68 inches or 175 pounds. The categories used to measure a variable make up a scale of measurement, and the relationships between the categories determine different types of scales. 4|Page PSYCHOLOGY SOCIETY  SAN MATEO MUNICIPAL COLLEGE (PSY 002) PSYCHOLOGICAL STATISTICS General Luna St., Guitnangbayan I, San Mateo, Rizal MRS. GINA T. MONTALLA Tel. No. (02) 997-9070 SCALES OF MEASUREMENT ❖ Nominal Scale ▪ A nominal scale consists of a set of categories that have different names. Measurements on a nominal scale label and categorize observations, but do not make any quantitative distinctions between observations. ▪ This is the most primitive level of measurement. It is used when we want to distinguish one object from another for identification purposes. In these level, we can only say that one level is different from another, but the amount of difference between them cannot be determined. We cannot tell that one is better or worse than the other. ▪ Examples: gender, nationality, religion, color of skin, religion, civil status, etc. ❖ Ordinal Scale ▪ An ordinal scale consists of a set of categories that are organized in an ordered sequence. Measurements on an ordinal scale rank observations in terms of size or magnitude. ▪ In the ordinal level of measurement, data are arranged in some specified order or rank. ▪ Examples: ranking of contestants, siblings in the family, honor students in a class, positions, social class, clothing size, etc. ❖ Interval Scale ▪ Interval scale has an arbitrary zero point. The value 0 is assigned to a particular location on the scale simply as a matter of convenience or reference. In particular, a value of zero does not indicate a total absence of the variable being measured. ▪ If the data are measured in interval level, we can say not only that the object is greater or less than the other but we can specify the amount of difference. ▪ Examples: scores in a test, temperature, IQ scores, score in standardized test, etc. ❖ Ratio Scale ▪ Ratio scale is anchored by a zero point that is not arbitrary but rather is a meaningful value representing none (a complete absence) of the variable being measured ▪ The ratio level of measurement is like the interval. The only difference is that the ratio level always starts from the absolute or true zero point. In addition, in the ratio level, there is always the presence of unit of measure. If the data is measured in this level, we can say that that the object is so many times as large or as small as the other. ▪ Examples: age, height, weight, length, time 5|Page PSYCHOLOGY SOCIETY  SAN MATEO MUNICIPAL COLLEGE (PSY 002) PSYCHOLOGICAL STATISTICS General Luna St., Guitnangbayan I, San Mateo, Rizal MRS. GINA T. MONTALLA Tel. No. (02) 997-9070 Survey responses can be measured by using the four types of scales. At times, it is possible to measure a response by more than one of these scales. The best type of scale to use will depend on two things: The nature of the variable you are studying. How much measurement precision you desire. The level of measurement needs to fit the variable being measured. Sometimes a nominal scale is sufficient. Physiological variables lend themselves to different levels of measurement because they represent a continuous dimension. Traits, attitudes, and preferences can be viewed as continuous dimensions, and each individual could fall at any point along each dimension. Researchers generally use the following rule for selecting level of measurement: When different level of measurement will “fit” equally well, choose the highest level possible because it provides more information about a response. Also, the various levels of measurement are analyzed with different statistical techniques, and the statistical test we can use for interval and ratio data are more powerful than those for nominal and ordinal data. Thus ratio and interval scales tend to be preferred by researchers over ordinal and nominal measurements DESCRIPTIVE AND INFERENTIAL STATISTICS Descriptive Statistics Descriptive statistics are statistical procedures used to summarize, organize, and simplify data. It is a technique that take the raw score and organize or summarize them in the form that is more manageable. Generally, descriptive statistics involves gathering, organizing and presenting, and describing data. Descriptive statistics includes those measures that may be used to describe a group in terms of variables being considered, such as measure of central tendency and measure of dispersion. Inferential Statistics Inferential Statistics consist of techniques that allows us to study samples and then make generalizations about the populations from which they were selected. Inferential Statistics involves decision-making based on data at hand and employing some statistical test SAMPLING ERROR ❖ It is the discrepancy, or amount of error, that exists between a sample statistic and the corresponding population parameter. ❖ It is the error that arises as a result of taking a sample from a population rather than using the whole population 6|Page PSYCHOLOGY SOCIETY  SAN MATEO MUNICIPAL COLLEGE (PSY 002) PSYCHOLOGICAL STATISTICS General Luna St., Guitnangbayan I, San Mateo, Rizal MRS. GINA T. MONTALLA Tel. No. (02) 997-9070 ❖ The sampling error for a given sample is unknown but when the sampling is random, the maximum likely size of the sampling error is called the margin of error ❖ Illustration: Two samples are selected from the same population. Notice that the sample statistics are different from one sample to another, and all the sample statistics are different from the corresponding population parameters. The natural differences that exist, by chance, between a sample statistic and a population parameter are called sampling error. NON-SAMPLING ERROR ❖ The error that arises in data collection process as a result of factors other than taking a sample ❖ Non sampling error have the potential to cause bias in polls, surveys, or samples. ❖ Examples: ▪ Bias in choosing samples ▪ Typographical errors/wordings used in questionnaire ▪ Undesirable answers in survey or poll ▪ Low response rate SAMPLING ❖ Sampling is the process of taking a sample from a population SAMPLING TECHNIQUE ❖ Sampling technique is the procedure used to determine the individuals or members of the sample. PROBABILITY SAMPLING ❖ It is a sampling technique wherein each member or element of the population has an equal chance of being selected as a member of the sample. ❖ It is therefore an assumption that when using probability sampling, the researcher should have a complete list of the members of the population. ❖ Probability sampling is sampling without bias because the selection of members of the sample is not predetermined ❖ Probability sampling is a sampling technique where a researcher sets a selection of a few criteria and chooses members of a population 7|Page PSYCHOLOGY SOCIETY  SAN MATEO MUNICIPAL COLLEGE (PSY 002) PSYCHOLOGICAL STATISTICS General Luna St., Guitnangbayan I, San Mateo, Rizal MRS. GINA T. MONTALLA Tel. No. (02) 997-9070 randomly. All the members have an equal opportunity to be a part of the sample with this selection parameter. ❖ Probability sampling is a sampling technique in which researchers choose samples from a larger population using a method based on the theory of probability. This sampling method considers every member of the population and forms samples based on a fixed process. ❖ For example, in a population of 1000 members, every member will have a 1/1000 chance of being selected to be a part of a sample. Probability sampling eliminates bias in the population and gives all members a fair chance to be included in the sample. Simple Random Sampling/Random Sampling o It is a technique of drawing sample whereby each element of the population has an equal chance of being taken into the sample. o This technique is the most commonly used especially if the population is homogenous with respect to a particular attributes or characteristics. o Example: Lottery, Table of random digits. o Simple random sampling: The most basic form of probability sampling is the simple random sample, in which a portion of the whole population is selected in unbiased way. One of the best probability sampling techniques that helps in saving time and resources, is the Simple Random Sampling method. It is a reliable method of obtaining information where every single member of a population is chosen randomly, merely by chance. Each individual has the same probability of being chosen to be a part of a sample. Systematic Sampling o It is a technique of choosing an element for every k elements of a 𝑁 population where k = 𝑛 , where N is the population size and n is the sample size o Systematic sampling: Researchers use the systematic sampling method to choose the sample members of a population at regular intervals. It requires the selection of a starting point for the sample and sample size that can be repeated at regular intervals. This type of sampling method has a predefined range, and hence this sampling technique is the least time-consuming. o For example, a researcher intends to collect a systematic sample of 500 people in a population of 5000. He/she numbers each element of the population from 1-5000 and will choose every 10th individual to be a part of the sample (Total population/ Sample Size = 5000/500 = 10). 8|Page PSYCHOLOGY SOCIETY  SAN MATEO MUNICIPAL COLLEGE (PSY 002) PSYCHOLOGICAL STATISTICS General Luna St., Guitnangbayan I, San Mateo, Rizal MRS. GINA T. MONTALLA Tel. No. (02) 997-9070 Stratified Sampling o It is a technique of dividing a population into groups, called strata, and sampling is done in each stratum. o Stratified random sampling is a method in which the researcher divides the population into smaller groups that don’t overlap but represent the entire population. While sampling, these groups can be organized and then draw a sample from each group separately. o The table below shows the sample size taken in the different strata considering equal allocation and proportional allocation. In this example, 30% of a population of 1000 families is to be taken Socio- Population Sample Size (n) economic Size (N) Equal Allocation Proportional Allocation Status (EA) (PA) High 150 100 45 Average 350 100 105 Low 500 100 150 Total 1000 300 300 Cluster Sampling o It is a technique of taking a sample from groups, and all the elements in those group chosen will form the sample o Cluster sampling is a method where the researchers divide the entire population into sections or clusters that represent a population. Clusters are identified and included in a sample based on demographic parameters like age, sex, location, etc. This makes it very simple for a survey creator to derive effective inference from the feedback. o For example, if the United States government wishes to evaluate the number of immigrants living in the Mainland US, they can divide it into clusters based on states such as California, Texas, Florida, Massachusetts, Colorado, Hawaii, etc. This way of conducting a survey will be more effective as the results will be organized into states and provide insightful immigration data. 9|Page PSYCHOLOGY SOCIETY  SAN MATEO MUNICIPAL COLLEGE (PSY 002) PSYCHOLOGICAL STATISTICS General Luna St., Guitnangbayan I, San Mateo, Rizal MRS. GINA T. MONTALLA Tel. No. (02) 997-9070 Multi-Stage Sampling o It is a sampling in various stage until the desired sampling units are obtained o It is used in studies that cover a wide geographical area or substantially large population Uses of probability sampling There are multiple uses of probability sampling. They are: ❖ Reduce Sample Bias: Using the probability sampling method, the bias in the sample derived from a population is negligible to non-existent. The selection of the sample mainly depicts the understanding and the inference of the researcher. Probability sampling leads to higher quality data collection as the sample appropriately represents the population. ❖ Diverse Population: When the population is vast and diverse, it is essential to have adequate representation so that the data is not skewed towards one demographic. For example, if Square would like to understand the people that could make their point-of-sale devices, a survey conducted from a sample of people across the NCR from different industries and socio-economic backgrounds helps. ❖ Create an Accurate Sample: Probability sampling helps the researchers plan and create an accurate sample. This helps to obtain well-defined data. NON-PROBABILITY SAMPLING ❖ It is a sampling technique wherein members of the sample are drawn from the population based on the judgement of the researcher. ❖ The results of a study using this sampling technique are relatively biased ❖ The technique lack objectivity of the selection; hence, it is sometimes called Subjective Sampling. ❖ Inferences made based on the sample obtained using this technique are not so reliable. ❖ In non-probability sampling, the researcher chooses members for research at random. This sampling method is not a fixed or predefined selection process. This makes it difficult for all elements of a population to have equal opportunities to be included in a sample. ❖ The non-probability method is a sampling method that involves a collection of feedback based on a researcher or statistician’s sample selection capabilities and not on a fixed selection process. In most situations, the output of a survey conducted with a non- probable sample leads to skewed results, which may not represent the desired target population. But, there are situations such as the preliminary stages of research or cost constraints for conducting research, where non-probability sampling will be much more useful than the other type. Convenience Sampling o As the name implies, convenience sampling is used because of the convenience it offers to the researcher. Although convenience sampling may be used occasionally, we cannot depend on it in making inferences about a population o This method is dependent on the ease of access to subjects such as surveying customers at a mall or passers-by on a busy street. It is usually termed as convenience sampling, because of the researcher’s ease of carrying it out and getting in touch with the subjects. Researchers have nearly no authority to select the sample elements, and it’s purely done based on proximity and not representativeness. This non-probability sampling method 10 | Page PSYCHOLOGY SOCIETY  SAN MATEO MUNICIPAL COLLEGE (PSY 002) PSYCHOLOGICAL STATISTICS General Luna St., Guitnangbayan I, San Mateo, Rizal MRS. GINA T. MONTALLA Tel. No. (02) 997-9070 is used when there are time and cost limitations in collecting feedback. In situations where there are resource limitations such as the initial stages of research, convenience sampling is used. o For example, startups and NGOs usually conduct convenience sampling at a mall to distribute leaflets of upcoming events or promotion of a cause – they do that by standing at the mall entrance and giving out pamphlets randomly. Purposive Sampling o It is a technique of choosing sampling units from a given population which have a specific characteristics o Purposive samples are formed by the discretion of the researcher. Researchers purely consider the purpose of the study, along with the understanding of the target audience. For instance, when researchers want to understand the thought process of people interested in studying for their master’s degree. The selection criteria will be: “Are you interested in doing your masters in …?” and those who Snowball sampling: o Snowball sampling is a sampling method that researchers apply when the subjects are difficult to trace. For example, it will be extremely challenging to survey shelter less people or illegal immigrants. In such cases, using the snowball theory, researchers can track a few categories to interview and derive results. Researchers also implement this sampling method in situations where the topic is highly sensitive and not openly discussed—for example, surveys to gather information about HIV Aids. Not many victims will readily respond to the questions. Still, researchers can contact people they might know or volunteers associated with the cause to get in touch with the victims and collect information. Quota Sampling o A technique of setting a sample size based on the nature of the data that are needed and taking the first sampling units that fulfill the required number or quota. o In Quota sampling, the selection of members in this sampling technique happens based on a pre-set standard. In this case, as a sample is formed based on specific attributes, the created sample will have the same qualities found in the total population. It is a rapid method of collecting samples. Uses of non-probability sampling Non-probability sampling is used for the following: ❖ Create a hypothesis: Researchers use the non-probability sampling method to create an assumption when limited to no prior information is available. This method helps with the immediate return of data and builds a base for further research. ❖ Exploratory research: Researchers use this sampling technique widely when conducting qualitative research, pilot studies, or exploratory research. 11 | Page PSYCHOLOGY SOCIETY  SAN MATEO MUNICIPAL COLLEGE (PSY 002) PSYCHOLOGICAL STATISTICS General Luna St., Guitnangbayan I, San Mateo, Rizal MRS. GINA T. MONTALLA Tel. No. (02) 997-9070 ❖ Budget and time constraints: The non-probability method when there are budget and time constraints, and some preliminary data must be collected. Since the survey design is not rigid, it is easier to pick respondents at random and have them, take the survey or questionnaire. How do you decide on the type of sampling to use? For any research, it is essential to choose a sampling method accurately to meet the goals of your study. The effectiveness of your sampling relies on various factors. Here are some steps expert researchers follow to decide the best sampling method. ❖ Jot down the research goals. Generally, it must be a combination of cost, precision, or accuracy. ❖ Identify the effective sampling techniques that might potentially achieve the research goals. ❖ Test each of these methods and examine whether they help in achieving your goal. ❖ Select the method that works best for the research. Determining the sample size ❖ To determine the sample size from a given population size, the Slovin’s Formula is used. 𝑁 n= 1+𝑁𝛼 2 where n = sample size N = population size 𝛼 = level of significance (allowable error in making a decision) ❖ The sample size is the smallest possible number that may constitute a good sample. ❖ Example: It is desired to conduct a survey on 5000 students of ABC College. What is the minimum sample size that may be drawn if an error of at most 5% is allowed? 1. Solution: N = 5 000 𝛼 = 0.05 5 000 n = 1+(5 000)(0.05)2 n = 370 LEARNING ACTIVITIES (Google Form) (Link) A. Write on the blank whether the data are discrete or continuous. 1. Scores in a test 2. Average of the final grades of students in all their subjects 3. Number of non-earning members in a family 4. Vehicles that pass a given point from 12:00 to 1:00 P.M. 5. Heights of all 15-year old students in your school 6. Weights of junior students in your school 7. Students living with relatives other than their parents 8. Daily allowances of high school students 9. Fractional part of a family's income spent for food 10. Area of residential lot owned by families of Grade VI pupils B. Write on the blank whether the data are metric, enumeration or categorical. 1. Self-esteem of senior high school students 2. Percent of plants that grow from a pack of seeds 3. Number of senior citizens in your barangay 4. Personal interrelationship among third year students 5. Growth of plants in one month, in terms of height 6. Attitude of parents towards the 3-day in a week classes 7. Grade 1 pupils who have preschool education 12 | Page PSYCHOLOGY SOCIETY  SAN MATEO MUNICIPAL COLLEGE (PSY 002) PSYCHOLOGICAL STATISTICS General Luna St., Guitnangbayan I, San Mateo, Rizal MRS. GINA T. MONTALLA Tel. No. (02) 997-9070 8. Average performance of incoming freshmen students in the entrance test 9. Intelligence quotient scores of freshmen high school students 10. Civil status of applicants for overseas work C. Identify the scale of measurement for each of the following: (nominal, ordinal, interval, and ratio) 1. Religion 2. IQ scores 3. Speed of a car 4. Civil status 5. Number of books in the library 6. Address 7. Size of a T-shirt 8. Land area 9. Salary of workers 10. Number of hours spent in studying D. Tell whether the following situation will make use of DESCRIPTIVE or INFERENTIAL statistics. 1. A teacher computes the average grade of her students and then determines the top ten students. 2. The manager of the business firm predicts future sales of the company based on the present sales. 3. A psychologist investigates if there is a significant relationship between the mental age and the chronological age. 4. A researcher studies the effectiveness of a new fertilizer to increasing food production. 5. A janitor counts the number of various furniture inside the school. 6. A sports journalist determines the most popular basketball player for this year. 7. A school administrator forecast future expansion of the school. 8. A market vendor investigates the most popular brand of vinegar. 9. An engineer calculate the average height of the building along Taft Avenue. 10. A dermatologist tests the relative effectiveness of a new brand of medicine in curing pimples and other skin diseases. E. Determine the sample size in each problem. 1. There are 2 000 housewives In Barangay Matahimik. It is desired to make a survey of their preferences for cooking fuel. How many housewives may at least be taken as respondents if an error of at most (a) 5% and (b) 2.5% in the decision maybe allowed? 2. A physician would like to study the effectiveness of a drug on patients with pulmonary disease. He is considering a population of 10 000 patients. What is the minimum sample size he could take if he could only allow (a) 1% and (b) 5% error for a conclusion to be made? 3. A researcher plans to conduct a survey. If the population is 8 000, find the sample size if the allowable error to make a conclusion is a. 10% b. 5% c. 1% d. 7.5% ASSESSMENT/ EVALUATION Quiz using Google form (link) 13 | Page PSYCHOLOGY SOCIETY  SAN MATEO MUNICIPAL COLLEGE (PSY 002) PSYCHOLOGICAL STATISTICS General Luna St., Guitnangbayan I, San Mateo, Rizal MRS. GINA T. MONTALLA Tel. No. (02) 997-9070 ASSIGNMENT 1. Study: Presentation of Data What is frequency distribution table? Describe the following: Simple Frequency Distribution Table Complete Frequency Distribution Table Relative Frequency Distribution Table Cumulative Frequency Distribution Table Cumulative Percentage Distribution Table Illustrate the graph of the following Bar chart Histogram Frequency Polygon Pie Chart Ogive LEARNING RESOURCES REFERENCES: Ferguson G. A. & Takane, Y. (1989). Statistical analysis in psychology and education. (6th Ed.) Singapore: McGraw Hill Book Co. Gravetter, F. J. & Walnau L. B., (2012). Statistics for behavioral sciences. Philippines: Cengage Learning Asia Pt. Ltd. Montero – Galliguez, T. C. Gaguing Jr., N. A., et. al., (2016). Fundamentals of statistical analysis. Manila: C & E Publishing, Inc. ONLINE RESOURCES: Brown, B. Prim's Algorithm: Minimal Spanning Tree. https://www.youtube.com/watch?v=YyLaRffCdk4 Fuscaldo, D. Personal Loans 101: Everything you need to know. Retrieved March 30, 2018 from https://www.bankrate.com/finance/loans/personal-loans-101.aspx. Kenny, T. Differences between stocks and bonds. Retrieved March 30, 2018 from https://www.thebalance.com/the-difference-between-stocks-and-bonds-417069. Bitcoin: How Cryptocurrencies Work, https://www.youtube.com/watch?v=kubGCSj5y3k 14 | Page PSYCHOLOGY SOCIETY