Psychological Statistics .pdf

PRELIM PERIOD consumer studies, about government spending CHAPTER I based on utilization studies, and so on. Objectives: Types of Statistics Demonstrate knowledge of stati...

PRELIM PERIOD consumer studies, about government spending CHAPTER I based on utilization studies, and so on. Objectives: Types of Statistics Demonstrate knowledge of statistical term. Differentiate between the two branches of 1. Descriptive Statistics - are all the methods used statistics. to collect, organize, summarize or present data, Identify types of data. usually to make the data easier to understand. It is Identify the measurement level for each variable. concerned with summary calculations such as Identify different sampling techniques averages, and percentages and construction of graphs, charts and tables. What is Statistics? 2. Inferential Statistics - is concerned with the The word statistics is derived from the Latin word formulation of conclusions or generalizations about status meaning "state". a population based on an observation or a series of observations of a sample drawn from a population. In the beginning, statistics involved compilation It consists of performing hypothesis testing, of data and graphs describing various aspects of a determining relationships among variables, and state or country. making predictions. To some, statistics means actual numbers derived Population vs. Sample from data and others refer to statistics as a method of analysis. A Population is the collection of all possible observations of a specified characteristic of Thus, specifically, statistics is defined as the interest. science of collecting, organizing, presenting, Example: All students in UPHS for the SY analyzing and interpreting numerical data for the 2024-2025. (As a whole) purpose of assisting in making a more effective decision. A Sample is a subset of the population. Example: First year students in UPHS. (certain Why Study Statistics? group in the the whole group like CAE, CIHM, and etc) Like professional people, you must be able to read and understand the various statistical studies Variables and Types of Data performed in your fields. To have this understanding, you must be knowledgeable about Qualitative Variables are non-numeric variables the vocabulary, symbols, concepts, and statistical and can't be measured. procedures used in these studies. Examples include gender (male, female), religious affiliation (Roman Catholic, Iglesia ni Cristo, You may be called on to conduct research in your Methodist, etc), ethnicity (Ilocano, Tagalog, field since statistical procedures are basic to Ibanag, etc.). (NOMINAL DATA AND research. To accomplish this, you must be able to ORDINAL DATA PANK DATA) design experiments; collect, organize, analyze, and summarize data; and possibly make reliable Quantitative Variables are numerical variables predictions or forecasts for future use. You must and can be measured. also be able to communicate the results of the study Examples include balance in your checking in your own words. account, and the number of children in your family. You can also use the knowledge gained from For example, the number of children in the family studying statistics to become better consumers and may be 1, 2, 3, or any other whole number but it citizens. For example, you can make intelligent can never be 1.25 or 0.5. Thus, this variable has decisions about what products to purchase based on values which can only be obtained through the process of counting and is referred to as discrete or discontinuous variables. (INTERVAL DATA AND RATIO DATA) Discrete variables - are values that are obtained by counting. The results are whole numbers. Data Collection Example, the number of students in the room. 1. Focus Group 2. Telephone Interview Continuous variables - are values that are 3. Mail Questionnaires obtained by measuring. The results can be any 4. Door-to-Door Survey value between two specific values. 5. Mail Intercept Example, if you take everyone's height of students 6. New Product Registration in the room, you could get any number between 7. Personal Interview two reasonable amounts. So height is a continuous 8. Experiments variable. Sources of Data Levels of Measurement 1. Nominal Data: The weakest data measurement. 1. Secondary Data: Data which are already Numbers are used to represent an item or available. characteristic. (can’t be counted nor measure but Example, UPHS enrollment data. Secondary data must be as a group) is less expensive; however, it may not satisfy the Examples include names, gender, religious researcher's need. affiliation, civil status, college majors. Note that such data should not be treated as numerical, since 2. Primary Data: Data which must be collected. relative size has no meaning Sampling Techniques 2. Ordinal or Pank Data: This can be ordered or ranked, but a specific difference in the levels can Sampling Techniques are used when a part of the not be determined. population is to be surveyed. Example, the performance rating (Outstanding, If it takes too long or very expensive to interview Very Satisfactory, Satisfactory, Poor). This can be the whole population, a sample is used. ordered. If a sample is chosen correctly to represent the population, it is called mbla while if it does not 3. Interval Data: This can be ordered and has represent the whole population, it is called bicod. exact difference between any two units but has no There are many ways to collect a sample, meaningful zero or starting point. statistical or non-statistical. Example, Temperature is an interval data since Statistical Sampling Techniques they can be ordered, there is an exact difference between two degrees, but the zero does not mean 1. Simple Random Sampling: This is used to see the starting point since there can be temperatures that all possible elements of the population have an below zero. equal opportunity of being selected for the sample. Example: lahat mag susurvey pero kunwari 30 and 4. Ratio Data: Is the highest level of measurement nag survey pero 15 sample lang need ko so and allows for all basic arithmetic operations, mamimili ako sa 30 na yun para ma complete ko including division and multiplication. Data at this yung 15 na sample survey na need ko or as a whole level can be ordered, has exact difference between dapat kukuhanan ng survey units, and has a meaningful zero. 2. Stratified Random Sampling: This is obtained Example, height, weight, and time. by selecting simple random samples from strata (or mutually exclusive sets). Some of the criteria for dividing a population into strata are: Gender (male, female); Age (under 18, 18 to 28, 29 to 39); Occupation (blue-collar, professional, other) Chapter 2: FREQUENCY DISTRIBUTIONS Example: per category not a whole not like simple random AND GRAPHS sampling Frequency Distribution 3. Cluster Sampling: This is a simple random sample of groups or cluster of elements. Cluster A frequency distribution is the sampling is useful when it is difficult or costly to organization of raw data in table form, generate a simple random sample. using classes and frequencies. Example: the whole brgy of Cauayan but will only be choosing a sample per cluster not the whole A frequency distribution is a table used to barangay in the Cauayan describe a data set. 4. Systematic Sampling: Researchers obtain It summarizes data by telling how many systematic samples by numbering each subject of frequencies appear in each group or class. the population and then selecting every kth subject. Example: my sinusundan akong number na pipiliin A categorical frequency distribution is kong sample like gusto ko puro number 2 lang ang used for nominal data and lists the pipiliin kong sample ko categories and tells how many are in the category. Non-Statistical Sampling Techniques Numerical data can be presented in 1. Judgement Sampling: In this case, the person ungrouped or grouped frequency taking the sample has direct or indirect control over distribution. which items are selected for the sample. Example: walang control basta gusto lang kitang Frequency Distribution gamitin as my example or respondent ko An ungrouped frequency distribution lists 2. Convenience Sampling: In this method, the each number and the frequency for that decision maker selects a sample from the number. population in a manner that is relatively easy and convenient. A grouped frequency distribution gives Example: kung ano yung pinaka convenient from several classes and the frequencies for the word it self para di mahirapan o lumayo mag each class. hanap ng respondent and sample To decide whether to use ungrouped or 3. Quota Sampling. In this method, the decision grouped frequency distribution, find the maker requires the sample to contain a certain range. number of items with a given characteristic. Many political polls are, in part, quota sampling. A range is the highest number minus the Example: pag nakuha na yung need na respondent lowest number in the data set. If the range is stop na hindi na kaylangan pang sumobra is small, use an ungrouped frequency distribution Yung makukuha sapag subtract sa highest to lowest ay gagamitn sapag plus sa lower unit para makuha si 205 and it follows then para sa upper unit kukunin mo yung 2nd sa lower unit tapos isusubract mo lang sa 1 lahat and it also follows