The document introduces hypothesis-driven thinking. It discusses that hypothesis-driven thinking is a way of thinking about the overall framework and conclusions of a problem with limited information and time. Hypothesis-driven thinking is similar to abduction, which forces oneself to think about the possible causes of a problem. It emphasizes building hypotheses first before experiments to verify hypotheses. Seeing the overall picture is important for taking action.
The document introduces hypothesis-driven thinking. It discusses that hypothesis-driven thinking is a way of thinking about the overall framework and conclusions of a problem with limited information and time. Hypothesis-driven thinking is similar to abduction, which forces oneself to think about the possible causes of a problem. It emphasizes building hypotheses first before experiments to verify hypotheses. Seeing the overall picture is important for taking action.
This document summarizes key aspects of observational and archival research methods from Chapter 8 of the book "Research Methods, 9th Edition". It discusses that in non-experimental research, hypotheses may be generated inductively through observation and modified over time as new data is collected. It also outlines methods for recording observational data such as field notes, checklists, and recording devices. Content analysis is described as evaluating hypotheses using publicly available language and images by measuring the frequency of words/themes or determining themes. Rater reliability with multiple coders is important.
This chapter discusses non-experimental research methods, including observational research, archival research, and case study research. Observational research involves observing and recording behavior without manipulating variables. Archival research examines existing records to obtain data and test hypotheses. Case study research explores a unique situation, individual, or group in depth using various research methods like observation and interviews. These non-experimental methods cannot prove causation but can identify correlational relationships.
This document discusses key concepts in inferential statistics, including sampling distributions, hypothesis testing, significance, effect size, power, chi-square tests, analysis of variance (ANOVA), and t-tests. It explains that inferential statistics are used to draw conclusions about populations based on samples, and covers topics like the standard error of the mean, properties of sampling distributions, null and alternative hypotheses, one-tailed and two-tailed tests, and how to interpret ANOVA tables.
This chapter discusses data exploration techniques including preparing data for analysis, data reduction, coding data, and descriptive statistics. Key points covered include putting data in a summary sheet, checking for invalid, missing, and outlier data, describing data numerically and graphically, and using tables, graphs, and measures of central tendency and variability to summarize and explore relationships in the data. Common graphs discussed are histograms, frequency polygons, scatterplots, line graphs, bar graphs, and box plots.
The document describes three different methodologies used in research studies:
1) A simple random sampling technique was used to select 10,000 subscribers out of 170,000 total for an online survey about a property developer's portal.
2) Companies for one study were selected from the Fortune 500 list to include large global corporations that are leaders in information technology.
3) A purposive sampling method was used to select 600 senior executives from a directory of top computer executives in the eastern US based on their job titles related to strategic planning.
This document summarizes key aspects of observational and archival research methods from Chapter 8 of the book "Research Methods, 9th Edition". It discusses that in non-experimental research, hypotheses may be generated inductively through observation and modified over time as new data is collected. It also outlines methods for recording observational data such as field notes, checklists, and recording devices. Content analysis is described as evaluating hypotheses using publicly available language and images by measuring the frequency of words/themes or determining themes. Rater reliability with multiple coders is important.
This chapter discusses non-experimental research methods, including observational research, archival research, and case study research. Observational research involves observing and recording behavior without manipulating variables. Archival research examines existing records to obtain data and test hypotheses. Case study research explores a unique situation, individual, or group in depth using various research methods like observation and interviews. These non-experimental methods cannot prove causation but can identify correlational relationships.
This document discusses key concepts in inferential statistics, including sampling distributions, hypothesis testing, significance, effect size, power, chi-square tests, analysis of variance (ANOVA), and t-tests. It explains that inferential statistics are used to draw conclusions about populations based on samples, and covers topics like the standard error of the mean, properties of sampling distributions, null and alternative hypotheses, one-tailed and two-tailed tests, and how to interpret ANOVA tables.
This chapter discusses data exploration techniques including preparing data for analysis through data reduction, coding, and descriptive statistics. Graphic and descriptive techniques are used to summarize and describe data numerically and graphically. Common graphs discussed are frequency distributions, scatterplots, line graphs, bar graphs, and box-and-whisker plots which can show relationships between variables and the distribution of data. Checks for invalid, missing, and outlier data are recommended before conducting inferential statistical analyses.
45. 6 樣本大小的決定
2. 最適分配法:在某些情況下,可能各層的抽樣 單
位成本均不同。故在總樣本數已知,各層抽樣成
本不同,各層變異數不同時,適合採用最適分
配。其公式如下:
n :為總樣本數 ni :為第 i 層之最適樣本數
Ni :為第 i 層所含母體數
σi :為第 i 層的標準差
∑
⋅⋅
=
ii
ii
N
Nn
n
σ
σ
1