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LỌC SỐ LIỆU TRONG SPSS
1.Số liệu đơn giản: • Dùng Sort cases : 1.Vào file dữ liệu trong Data Editor 2.Vào các folder: ➢ Data ➢ Sort cases ➢ Chọn tên biến cần kiểm tra ➢ Chọn Ascending hay Descending 2.( Dùng Find để tìm và sửa lỗi: Mở Data view, chọn biến cần sửa, trong Edit chọn Find, nhập giá trị biến cần sửa để tìm số liệu đã nhập sai và sửa (nên tìm ID để kiểm tra)

3. Dùng Frequencies: 1.Vào file dữ liệu trong Data Editor
+ Vào các folder:
* Analysis/Discreptive Statistics/Frequencies ➢ Rà sóat giá trị của biến theo Frequencies hay Tables of Frequencies để tìm số liệu nhầm lẫn ➢ Có thể dùng Find (Edit, Find, tên biến) để tìm và sửa lỗi 3.( Rà sóat giá trị của biến theo Frequencies hay Tables of frequencies để tìm số liệu nhầm lẫn ( Dùng Find (Edit, Find, tên biến) để tìm và sửa lỗi

2.Số liệu phức tạp • Dùng Select cases để tìm lỗi logic : vào Data Editor ➢ Data, Select cases, Chọn biến ➢ Chọn If condition is satisfied ➢ ➢ Chọn If, chọn biến và điều kiện của biến vào cột phải ➢ Continue, OK ← Ở Data Editor, xem cột ngoài cùng bên trái: các phiếu có gạch chéo là không được xử lý
( Muốn trở lại trạng thái ban đầu dùng All cases • Dùng Select cases để tìm lỗi logic : vào Data Editor 1. Data, Select cases, Chọn biến 2. Chọn If condition is satisfied/ 3. 3. If…. Ví dụ trong quá trình nhập gới: nam là 1; nữ là 2. Nhưng trong quá trình nhập có thể nhâp lộn số là 3,4,8…. Để kiếm tra xem có nhập lộn số hay không ta đặt điều kiện cho biến số để phát hiện sai sót trong quá trình nhập: bằng cách ta nhập điều kiện của giới vào ô Chọn If, chọn điều kiện của biến vào cột phải

Lưu ý: đối với biến định tính phải để trong ngoặc kép.
Hoặc

➢ Continue, OK ← Ở Data Editor, xem cột ngoài cùng bên trái: các phiếu có gạch chéo là các phiếu không thỏa mãn điều kiện trên sẽ không được xử lý. Thiếu dữ liệu (thiếu mẫu NC) Muốn trở lại trạng thái ban đầu : dùng All cases

3. Dùng Crostab để tìm lỗi:

• Vào Data Editor, chọn Crostab bằng: (Analyze, Discreptive Statistics, Crostab ( Nhập biến vào Row và Column (nên nhập thêm ID) ( Statistics, Continue, OK ( Tìm theo ID để sửa lỗi

XÁC ĐỊNH SỐ LƯỢNG, TỶ LỆ BIẾN ĐỊNH TÍNH

1. Biến đơn: xác định số lượng, tỷ lệ: Analyze- Discreptive Statistics- frequencies- chọn loại biến: (giới)- chọn Chart chọn –none- chọn Continue- OK

2. Biến kép : xác định số lượng, tỷ lệ một biến số theo tính chất: ví dụ: tính từng nhóm thể lực theo giới tính

Analyze- Discreptive Statistics-Crosstables- chọn biến xác định vào ROW, chọn biến tính chất vào Column – Vào CELL chọn các giá trị liên quan: Obcerved, row, column, total…
-Continue- OK

XÁC ĐỊNH SỐ LƯỢNG, GIÁ TRỊ TRUNG BÌNH, ĐỘ LỆCH CHUẨN BIẾN ĐỊNH LƯỢNG 1. Xác định giá trị trung bình và độ lệch chuẩn MỘT BIẾN ĐỊNH LƯỢNG LIÊN TỤC đơn giản: 1.Vào Data view 2.Analyse/ Descriptive Statistics/ Descriptive 3.Chọn biến cần xác định 4.Trong Option chọn giá trị cần tìm: mean, SD, SE,… 5. OK

2. BIẾN SỐ ĐỊNH LƯỢNG XĐ SỐ TRUNG BÌNH và ĐỘ LỆCH CHUẨN theo tính chất 1.Analyse/Compare Means/Means 2.Chọn biến cần xác định vào ô Dependent (phụ thuộc) tuổi 3.Chọn biến xác định tính chất vào ô Independent (độc lập) giới 4.Tùy chọn Option: + Chọn Means, SD,.. Qua ô Cell Statistics + Continue/OK

VẼ BIỂU ĐỒ
CHIA THÀNH NHIỀU NHÓM TÍNH TỶ LỆ THEO NHÓM

TRANSFORM/Recode/Into defferent variables
Nhập biến cần chia nhóm vào ô: String variables/Output variables: ví dụ:tuổi Nhómt3 (Label: nhóm tuổi) chọn change: tuổi Nhómt3
Chọn Old and new value vào new value nhập giá trị nhóm mới: nhom1/ vao Range nhập gia trị nhóm1: vd 1 thoguh 30 hoặc Range lowest trough 31 nhom2 31 thoguh 50/nhom3 Range highest trough 51 + Continue/OK

Ví dụ: Nếu nhiều nhóm xếp vào một nhóm thì xếp như sau: vd muốn xếp: Mù chữ, TH – Học vấn thấp THCS, THPT -Học vấn thấp trung bình Cđẳng, ĐH – Học vấn cao ta làm như sau:

Vào Old value chọn số 0 (mù chữ) vào New value chọn HV thap 1 (tiểu học) vào New value chọn HV thap
Vào Old value chọn số 2 (mù chữ) vào New value chọn HVtb 3 (THCS) vào New value chọn HVtb
Vào Old value chọn số 4 (THPT) vào New value chọn HVcao
Vào Old value chọn số 5 (CD,DH) vào New value chọn HVcao

+ Continue/OK TÍNH TỶ LỆ THEO NHÓM 1. BiẾN ĐƠN: Dùng Frequencies: Vào file dữ liệu trong Data Editor Analysis/Discreptive Statistics/Frequencies Chọn các giá trị trong bảng Frequencies: 2. BIẾN KÉP: xác định số lượng, tỷ lệ một biến số theo tính chất: ví dụ: tính từng nhóm thể lực theo giới tính
Analyze- Discreptive Statistics-Crosstables- chọn biến xác định vào ROW, chọn biến tính chất vào Column – Vào CELL chọn các giá trị liên quan: Obcerved, row, column, total…
-Continue- OK

LỆNH COMPUTE
Xây dựng 1 biến mới trên cơ sở các biến đã có:
VD:
[pic]

Transform/Compute/Target Variable: Đặt tên biến mới: BMI/ vào Type & Label dán nhãn cho biến mới/ dùng các phím chức năng (Function) để nhập công thức tính vào ô Mumeric Expression/OK

LỆNH COUNT: để tính toán (đếm) các giá trị của biến số:
Trước khi tính toán phải chuyển từ biến định tính sang biến định lượng
Transform/Counnt
Đặt tên biến cần tính giá trị vào ô Target Variable/ Đưa biến cần tổng hợp tính toán (đếm) vào ô Numeric Variable/Chọn Define Value, đưa giá trị cần xác định (cần đếm) vào Value (Vd: Muốn đếm giá trị có nghe đài số1/(không nghe đài số 2) thì ta nhập vào ô Value số 1) để đếm tất cả số 1 trên các biến cần đếm) /chọn Add/+ Continue/OK

CHU Ý: Với biến định tính (String) muốn dùng lệnh COUNT phải chuyển đổi thành biến định lượng (numeric) rồi mới ĐẾM được:

VD: nghe radio, đọc báo, biến trinhdo (String) trước muốn xếp nhóm phải đổi thành biến định lượng (numeric).

chia3nhomtuoi
| |Frequency |Percent |Valid Percent |Cumulative Percentf |
| |Số lượng |Tỷ lệ % | |Tỷ lệ cộng dôn |
|Valid | |1 |.5 |.5 |.5 |
| |nhom1 |37 |17.6 |17.6 |18.1 |
| |nhom2 |121 |57.6 |57.6 |75.7 |
| |nhom3 |51 |24.3 |24.3 |100.0 |
| |Total |210 |100.0 |100.0 | |

Nhóm tuổi theo giới nào có tỷ lệ Nam cao nhất? Vào anlyz-Descriptive- crosstable

[pic] 8nhomtuoi

| |Frequency |Percent |Valid Percent |Cumulative Percent |
|Valid |nhom1 |12 |5.7 |5.7 |5.7 |
| |nhom2 |10 |4.8 |4.8 |10.5 |
| |nhom3 |39 |18.6 |18.6 |29.0 |
| |nhom5 |33 |15.7 |15.7 |44.8 |
| |nhom6 |35 |16.7 |16.7 |61.4 |
| |nhom7 |30 |14.3 |14.3 |75.7 |
| |nhom8 |51 |24.3 |24.3 |100.0 |
| |Total |210 |100.0 |100.0 | |

[pic]

3 nhom trinh do hoc van

| |Frequency |Percent |Valid Percent |Cumulative Percent |
|Valid |hocvantb |153 |72.9 |72.9 |72.9 |
| |hocvanth |38 |18.1 |18.1 |91.0 |
| |ocvancao |19 |9.0 |9.0 |100.0 |
| |Total |210 |100.0 |100.0 | |

[pic] Case Processing Summary

| |Cases |
| |Valid |Missing |Total |
| |N |Percent |N |
| | |nam |nu | |
|3 nhom trinh do hoc|hocvantb |Count |88 |65 |153 |
|van | | | | | |
| | |% within 3 nhom |57.5% |42.5% |100.0% |
| | |trinh do hoc van | | | |
| |hocvanth |Count |18 |20 |38 |
| | |% within 3 nhom |47.4% |52.6% |100.0% |
| | |trinh do hoc van | | | |
| |ocvancao |Count |8 |11 |19 |
| | |% within 3 nhom |42.1% |57.9% |100.0% |
| | |trinh do hoc van | | | |
|Total |Count |114 |96 |210 |
| |% within 3 nhom |54.3% |45.7% |100.0% |
| |trinh do hoc van | | | |

chia nhom3

| |Frequency |Percent |Valid Percent |Cumulative Percent |
|Valid |nhom1 |133 |63.3 |63.3 |63.3 |
| |nhom2 |27 |12.9 |12.9 |76.2 |
| |nhom3 |50 |23.8 |23.8 |100.0 |
| |Total |210 |100.0 |100.0 | |

chia nhom3 * GIOI Crosstabulation

| | |GIOI |Total |
| | |nam |nu | |
|chia nhom3 |nhom1 |Count |70 |63 |133 |
| | |Expected Count |72.2 |60.8 |133.0 |
| | |% within chia |52.6% |47.4% |100.0% |
| | |nhom3 | | | |
| | |% within GIOI |61.4% |65.6% |63.3% |
| | |% of Total |33.3% |30.0% |63.3% |
| |nhom2 |Count |15 |12 |27 |
| | |Expected Count |14.7 |12.3 |27.0 |
| | |% within chia |55.6% |44.4% |100.0% |
| | |nhom3 | | | |
| | |% within GIOI |13.2% |12.5% |12.9% |
| | |% of Total |7.1% |5.7% |12.9% |
| |nhom3 |Count |29 |21 |50 |
| | |Expected Count |27.1 |22.9 |50.0 |
| | |% within chia |58.0% |42.0% |100.0% |
| | |nhom3 | | | |
| | |% within GIOI |25.4% |21.9% |23.8% |
| | |% of Total |13.8% |10.0% |23.8% |
|Total |Count |114 |96 |210 |
| |Expected Count |114.0 |96.0 |210.0 |
| |% within chia |54.3% |45.7% |100.0% |
| |nhom3 | | | |
| |% within GIOI |100.0% |100.0% |100.0% |
| |% of Total |54.3% |45.7% |100.0% |

[pic]

Uỏi ứng dụng compute tinh tuổi

Snthongtin a chia nhom3

| |Frequency |Percent |Valid Percent |Cumulative Percent |
|Valid |nhom1 |133 |63.3 |63.3 |63.3 |
| |nhom2 |27 |12.9 |12.9 |76.2 |
| |nhom3 |50 |23.8 |23.8 |100.0 |
| |Total |210 |100.0 |100.0 | |

Count

[pic]

KIỂM ĐỊNH CÁC TRUNG BÌNH 1.Kiểm định 1 trung bình lý thuyết với 1 trung bình nghiên cứu: Mở file dữ liệu-Analyse/Compare Means/One-Samples T-test (1TB lý thuyết và 1 TB NC)/Chọn biến cần kiểm định / Xác định giá trị cần kiểm định: Test value/xác định độ tin cậy bằng Option chọn Confidence Interval 95% (mặc định)/chọn Exact/Continue/OK Kết luận: Dựa vào Bảng Test Value/cột Sig.(2-tailed) giá trị P=… Nếu (Vì) p=….>0,05 nên không có sự khác biệt giữa ….trung bình của nhóm N/cứu so với TB lý thuyết với độ tin cậy….(95%)

2.Kiểm định 2 trung bình Mở file dữ liệu-Analyse/Compare Means/Independent--Samples T-test /Chọn biến cần kiểm định / Test variable: TUỔI (biến định lượng)/Grouping variable: GIỚI (biến định tính)/ Define group (1: nam; 2 nữ)/ /Continue/OK Kết luận: Dựa vào Bảng Independent Test / Đọc dựa vào cột: Levene’s Test for Equality of Variances (dùng cho 2 test có 2 Phương sai tương đương): * Nếu 1. Đọc Levene’s Test: vì Sig = 0,626>0,05 nên hai phương sai là tương đương- Tiếp theo đọc kết quả ở cột t-test for Equality ở Dòng 1 Equal variances assumed ( đọc cho trường hợp 2 giá trị trung bình có Phương sai/độ lệch chuẩn tương đương), 2. Dòng 1: (tại cột Sig.2-tailed) có Sig.2-tailed = 0,354>0,05 nên trung bình tuổi của 2 nhóm nam và nữ là không khác biệt với độ tin cậy 95% * Nếu Đọc Levene’s Test: vì Sig = …2 trung bình: Oneway ANOVA Mở file dữ liệu-Analyse/Compare Means/one-way ANOVA/Chọn biến định lượng cần kiểm định để đưa vào ô Dependent list (cân nặng)/ Chọn biến phân loại cần kiểm định để đưa vào ô Factor (nơi ở)/ - Chọn Option: để có giá trị trung bình các nhóm: + Chọn Descriptive; + Chọn Homogeneity of Variances/ 2 sự lựa chọn này nhằm xác định loại thống kê mô tả và tính đồng nhất của phương sai giúp kiểm định sự ngang bằng về phương sai giữa các nhóm (test thống kê Leven quyết định đến sự lựa chọn phương pháp kiểm định trong phần Post Hoc); Công cụ: Means Plot dùng để hiển thị đồ thị về giá trị trung bình của các nhóm; Công cụ:Missing Value dùng để kiểm soát giá trị khuyết: Exclude cases analysis by analysis: những trường hợp có giá trị khuyết ở trong biến phụ thuộc và biến kiểm soát sẽ không được đưa vào trong kiểm định. Ngoài ra những trường hợp có giá trị quan sát nằm bên ngoài chuỗi đã xác định cho biến kiểm soát cũng không được sử dụng. Exclude cases listwise: những trường hợp có giá trị khuyết cases trong biến điều khiển hoặc bất kỳ biến phụ thuộc nào được đưa ra hoặc không được đưa ra kiểm định đề bị loại trừ ra khỏi quá trình phân tích
( Trong tổng thể các phương sai của các mẫu dữ liệu phải tương đương (sẽ được kiểm định bằng test thống kê Levene’s Homogeneity of Variances) - Chọn Post Hoc: để so sánh sự khác biệt từng cặp giữa các nhóm (nhóm nào khác biệt với nhóm nào): + Chọn LSD nếu các phương sai bằng nhau; + Chọn Dunnett’ T3 nếu phương sai không bằng nhau /Continue/OK (không chọn Contracts)? Đọc kết quả: Dựa vào 2 Test sau: 1. Test thống kê Levene’s Homogeneity of Variances): Nếu: Sig. = p= >0,05 các phương sai tương đương – đọc kết quả bằng Test LSD ; Nếu: Sig. = p= 0,05 nên ta chấp nhận giả thuyết Ho nghĩa là không có sự khác biệt (trung bình trọng lượng ở các vùng sinh sống) với độ tin cậy 95 %

Lưu ý: + Nếu: Sig. = p= >0,05 các phương sai tương đương – đọc kết quả bằng Test LSD ; + Nếu: Sig. = p= 0,05 thì cũng không kết luận được mà phải dùng test khác để kiểm định 2. Kiểm định 2 tỷ lệ Mở file dữ liệu-Analyse/Descriptive Statistics/Crosstabs/ Chọn biến Phụ thuộc (hậu quả) (ví dụ xem tivi) cần Phân tích để đưa vào ô Row/ Chọn biến Độc lập (Nguyên nhân) (ví dụ: Giới: nam, nữ) cần Phân tích để đưa vào ô Column/ Chọn Cells: chọn Observed, chọn Row/Column/Total/ Chọn Statistics: chọn Chi-Quare/Chọn Exact/OK (Asymtotic only: có giá trị 95%) Kết luận: Để kết luận mối liên hệ giữa 2 biến độc lập hay phụ thuộc vào nhau ta dựa vào chỉ số Asymptotic Significance với số mẫu đủ lớn hoặc phân phối là phân phối chuẩn. Asym-Sig (p-value)= P=…> 0,05 (nên ta chấp nhận Ho) nghĩa là không có sự khác biệt (P

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...Chapter 1 Introduction Internet is changing the way consumers shop and buys goods and services, and has rapidly evolved into a global phenomenon. Many companies have started using the Internet with the aim of cutting marketing costs, thereby reducing the price of their products and services in order to stay ahead in highly competitive markets. Companies also use the Internet to convey, communicate and disseminate information, to sell the product, to take feedback and also to conduct satisfaction surveys with customers. Customers use the Internet not only to buy the product online, but also to compare prices, product features and after sale service facilities they will receive if they purchase the product from a particular store. Many experts are optimistic about the prospect of online business. In addition to the tremendous potential of the E-commerce market, the Internet provides a unique opportunity for companies to more efficiently reach existing and potential customers. Although most of the revenue of online transactions comes from business-to-business commerce, the practitioners of business-to-consumer commerce should not lose confidence. It has been more than a decade since business-to-consumer E-commerce first evolved. Scholars and practitioners of electronic commerce constantly strive to gain an improved insight into consumer behavior in cyberspace. Along with the development of E-retailing, researchers continue to explain E-consumers’ behavior from...

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...Jase Stubbs Chapter 2 discussion question 1/31/2016 1. Desired values are values about a persons self! Values that he or she want to reach as a person! Desired values are values that you want or “desire” as a person. It is a self achieving goals that we want for ourselves. A great example of a desired value to me would be that I value to save money to go on a vacation this year. So my desired outcome would be for me to save fifty dollars every week until my saving goal is achieved. Desirable on the other hand are things we want the world or society to achieve! To me a great example of desirable to me would be “World Peace.” It is a something that is ethical and standard classified by social norms. Everybody wants world peace, but it more or likely will not happen! 2. Hofstedes four original dimensions of culture are, •Power distance, the power distance is the distance of power within an organization etc. a place with a high power distance is like a communist country! The except who is in power and listen to what they say. A organization or place with a low power distance usually try to spread the power out amongst everybody, so there is no one absolute ruler. Everybody then has a say in what happens. • Collectivism vs. individualism, collectivism is like me counting on my best friend to be there for me when I need him and visa versa. Individualism would be like me depending on no one but myself! My fate rest in my hands! •masculinity vs femininity...

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...1. | Question : | (TCO 2) Almost always listed as important for leadership success is/are ____. | | | Student Answer: | | Basic intelligence | | | | Clear and strong values | | | | High level of personal energy | | | | All of the above | | | | Training | | Instructor Explanation: | p. 16 | | | | Points Received: | 3 of 3 | | Comments: | | | | 2. | Question : | (TCO 2) Vince Lombardi had a _____ personality; his followers' goal was to be equal to their understanding of his ____. | | | Student Answer: | | Schizophrenic; needs | | | | Mercurial; orders | | | | Stoic; desires | | | | Charismatic; values and goals | | | | Difficult; deficiencies | | Instructor Explanation: | p. 27 | | | | Points Received: | 3 of 3 | | Comments: | | | | 3. | Question : | (TCO 2) Regarding the importance of enthusiasm for leadership effectiveness, _____ said, "Good work is never done in cold blood; heat is needed to forge anything. Every great achievement is the story of a flaming heart." | | | Student Answer: | | Martin Luther King | | | | George Patton | | | | Harry Truman | | | | Colin Powell | | | | Eleanor Roosevelt | | Instructor Explanation: | p. 31 | | | | Points Received: | 3 of 3 | | Comments: | | | | 4. | Question : | (TCO 2) ____, ____, and _____ are traits found in charismatic leaders. | | | Student Answer:...

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...REPORT ON THE INTERACTIVE SESSION OF FINANCE & ACCOUNTS DEPARTMENT, CORPORATE AFFAIRS COMMISSION Venue: KEFFI HEALTH CLUB, KEFFI. Date : 23rd January 2010 Climate setting for the program was tuned by the Deputy Director Final Accounts/Mrs.B.F.Ikhanoba. Samuel Archibong offered the opening prayers. The DD/FA introduced the Senior Executives present. The Acting DFA/Mr. M.U.Wambai delivered the opening remarks with a word that the aim of the forum is to develop human capacity. Declaring the interactive session open the DFA emphasized on participation by all present. • The first paper was presented by the Senior Manager, Final Accounts/ K.M.Jemaku. Titled: FIXED ASSET MANAGEMENT – OPERATION & CHALLENGES: It defined and classified fixed assets, their management, depreciation and disposal. The management of Fixed Assets was noted to be a huge challenge to Finance & Accounts Department because of the many lapses imminent. The Sun System Fixed Assets module captured most of the detail data identifying an asset, and provides information automatically. Each asset is then assigned a code to further give the required peculiarity in the database. The presenter identified the challenges as follows; - Time lag between coding and labeling of assets. - Difficulty in tracing assets to assigned locations. - Failure to code some assets making disposal difficult. - Inability to reconcile physical assets with the register. Other issues relating to management of Fixed...

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...Biography of Dr. Victor O.K. Li Victor O.K. Li Chair of Information Engineering, Associate Dean of Engineering and Acting Head of Department Education: SB, SM, EE, ScD MIT; F.I.E.E.E., F.I.A.E., F.H.K.I.E. Victor O.K. Li received SB, SM, EE and ScD degrees in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology, Cambridge, Massachusetts, in 1977, 1979, 1980, and 1981, respectively. He joined the University of Southern California (USC), Los Angeles, California, USA in February 1981, and became Professor of Electrical Engineering and Director of the USC Communication Sciences Institute. Since September 1997 he has been with the University of Hong Kong, Hong Kong, where he is Associate Dean (Research) of Engineering, and Chair Professor of Information Engineering at the Department of Electrical and Electronic Engineering. He has also served as Managing Director of Versitech Ltd. the technology transfer and commercial arm of the University, and on various corporate boards. His research is in information technology, including all-optical networks, wireless networks, and Internet technologies and applications. Sought by government, industry, and academic organizations, he has lectured and consulted extensively around the world. Prof. Li chaired the Computer Communications Technical Committee of the IEEE Communications Society 1987-1989, and the Los Angeles Chapter of the IEEE Information Theory Group 1983-1985. He co-founded the International...

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...Curriculum Vitae of Gosiame Sheila Mokwena Contact information: Name: Gosiame Sheila Mokwena Address: 37 Hoopoe crescents 619 Willow Acres Silver lakes Pretoria 0095 Telephone: 012 809 1573 Cell Phone: 076 674 2679 Email: g29635277@gmail.com Personal information: Date of birth: 1990-05-13 Place of birth: Mamelodi, Pretoria Citizenship: South African Gender: Female Employment history: Position: Canvasing agent Company: Junkmail Duration: March 2010 – June 2011 Responsibilities: * Telephone potential customers * Campaigning purchases for the company Skills: * Written and verbal communication skills * Interpersonal skills Reference: Zelda – 0711869047(Team leader) Position: Promoter/Ambassador Company: Mabatho events Duration: July 2011 – March 2012 Responsibilities: * Market a brand, product or service * Interacting with customers, sales prospects, business partners and the media * Provide information about a brand, product or service * Generate sales opportunities * Build consumer preference Skills: * Verbal communication and social skills * Interpersonal skills Reference: Kay - 079 897 9056 (Team leader) Position: Promoters/Ambassadors Manager Company: Glam Monkey Duration: February 2011 – April 2012 Responsibilities: • Recruit promoters • Select promoters • Delegate duties • Organise transportation • Oversee activations and duties Skills: • Management • Delegation skills Reference: Lerato 076 710 3485(Head of management) Position:...

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...EasyPC Training Accounting Basics Business & Administration Contents Accounting Basics .............................................................................................................. 3 The Accounting Equation ................................................................................................. 3 Assets.................................................................................................................................. 3 Liabilities............................................................................................................................. 3 Owner’s Equity................................................................................................................... 3 The Balance Sheet .............................................................................................................. 5 Double Entry Bookkeeping............................................................................................... 6 Ledger Accounts................................................................................................................ 6 Trial Balance ...................................................................................................................... 7 Profit and Loss account.................................................................................................... 8 Sales................................................................................................................

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...Dare To Believe, Then Command “Verily, verily, I say unto you; He that believeth on Me, the works that I do shall he do also: and greater works than these shall he do; because I go unto My Father. And whatsoever ye shall ask in My name, that will I do, that the Father may be glorified in the Son. If ye shall ask any thing in My name, I will do it.” John 14:12-14. Jesus is speaking here, and the Spirit of God can take these words of His and make them real to us. “He that believeth on Me… greater works than these shall he do.” What a word! Is it true? If you want the truth, where will you get it? “Thy word is truth,” Christ said to the Father. When you take up God’s Word you get the truth. God is not the author of confusion or error, but He sends forth His light and truth to lead us into His holy habitation, where we receive a revelation of the truth like unto the noon day in all its clearness. The Word of God works effectually in us as we believe it. It changes us and brings us into new fellowship with the Father, with the Son, and with the Holy Spirit, into a holy communion, into an unwavering faith, into a mighty assurance, and it will make us partakers of the very nature and likeness of God as we receive His great and exceeding precious promises and believe them. Faith cometh by hearing, and hearing by the Word of God. Faith is the operative power. We read that Christ opened the understanding of His disciples, and He will open up our understanding and our hearts and will...

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...OM, Anderson, Fall 2014 1 Discussion Questions (Week 6) THE GOAL Chap 1 – 15 1. Do you perceive that the people at the Bearington plant were like most manufacturing people in most companies? 2. Do you feel that the Bearington plant has the right equipment and technology to do the job? 3. What is the “Goal”? How is it related to the three performance measurements: NP, ROI & CF? Why does Alex need another set of measurement: Throughput, Inventory, OE? 4. How is "productivity" defined traditionally? How does Jonah define "productivity"? 5. How does Jonah define "Throughput", "Inventory", and "Operating Expense"? How are these definitions different from traditional definitions? 6. Using the robots as an example, explain: (1) How the standard cost system defines "efficiency" (2) How high efficiency could lead to local optimum 7. What are those three questions that Jonah asked Alex about the productivity of the robots? 8. Using the analogy between the hiking and a manufacturing operation, explain the phenomena of “dependent events” and “statistical fluctuations”. Explain what a “balanced plant” is and explain why it would not work. 9. Using the dice game to explain the phenomena of “dependent events” and “statistical fluctuations”. Explain why a “balanced plant” would not work. 10. Explain another real-life example to describe the phenomena of “dependent events” and “statistical fluctuations”? 11. The hiking did not go very well first...

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...MODUL PANDUAN ASSESSMENT III STUDI LAPANGAN MANAJEMEN SUMBER DAYA MANUSIA PROGRAM STUDI ILMU MANAJEMEN 2015 DAFTAR ISI DAFTAR ISI ................................................................................................................................................ 2 PENDAHULUAN ......................................................................................................................................... 3 TUJUAN DAN MANFAAT STUDI LAPANGAN .............................................................................................. 4 KATEGORI OBJEK STUDI LAPANGAN ......................................................................................................... 5 MATERI STUDI LAPANGAN ........................................................................................................................ 6 OUTLINE LAPORAN STUDI LAPANGAN ...................................................................................................... 5 ~2~ PENDAHULUAN Proses pembelajaran adalah proses yang di dalamnya terdapat kegiatan interaksi antara guru-siswa dan komunikasi timbal balik yang berlangsung dalam situasi edukatif untuk mencapai tujuan belajar (Rustaman, 2001:461). Dalam proses pembelajaran, guru dan siswa merupakan dua komponen yang tidak bisa dipisahkan. Antara dua komponen tersebut harus terjalin interaksi yang saling menunjang agar hasil belajar siswa dapat tercapai secara optimal. Menurut pendapat Bafadal (2005:11), pembelajaran dapat diartikan...

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...The Social Self Every individual has an inner self and an outer self. The inner self is that which is known only by the individual or person himself. Whereas the outer self is that which we let others know. The capacity for self reflection is necessary for people to feel as if they understand their own motives and emotions and the causes of their behaviour. The self is heavily influenced by social factors that is the way we manage ourselves is influenced by the people around us and the situation at the time. The A, B, C of the self could be examined in three major domains; that is the affective, the cognitive, the behavioural. From the cognitive domain one will ask questions like- How do people come to know themselves? How do the social self, self concept, self esteem, self presentation. They develop a self concept and maintain a stable sense of identity? From the affective or emotional domain, we will ask questions like: How do people present themselves to others? How do they regulate their actions according to interpersonal demands? What is the self? The self refers to a person’s inner being including the mind and spirit. Here, we are referring specifically to the ego which is the conscious self, the real person. A person’s nature or personalities are the personal qualities that make up one individual. For example, we usually say that he or she is not his/her cheerful self today. Self Concept (Cognitive Component) Although we usually talk about the self-concept as...

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...South-Eastern Europe Journal of Economics 2 (2006) 129-146 EXCHANGE RATE RISK MEASUREMENT AND MANAGEMENT: ISSUES AND APPROACHES FOR FIRMS MICHAEL G. PAPAIOANNOU, Ph.D. International Monetary Fund Abstract Measuring and managing exchange rate risk exposure is important for reducing a firm’s vulnerabilities from major exchange rate movements, which could adversely affect profit margins and the value of assets. This paper reviews the traditional types of exchange rate risk faced by firms, namely transaction, translation and economic risks, presents the VaR approach as the currently predominant method of measuring a firm’s exchange rate risk exposure, and examines the main advantages and disadvantages of various exchange rate risk management strategies, including tactical vs. strategical and passive vs. active hedging. In addition, it outlines a set of widely-accepted best practices in managing currency risk and presents some of the main hedging instruments in the OTC and exchange-traded markets. The paper also provides some data on the use of financial derivatives instruments, and hedging practices by US firms. JEL Classification: F31, G13, G15, G32, M21 Keywords: Financial Risk, Financial Management, Foreign Exchange Hedging, Corporate Hedging Practices Corresponding address: 700 19th Street, N.W. Washington, DC 20431 e-mail: mpapaioannou@imf.org This paper draws heavily on various presentations on risk management while the author was the Director of Foreign...

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