thong ke trong kinh doanh- excel

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NGUYN DUY TM

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NI DUNG

Con ngi Tm nhn mi

Nhp d liu vo excel Thng k d liu dng bng Thng k d liu dng th 4. Thng k d liu bng cc i lng thng k m t 5. c lng v kim nh gi thit 6. Phn tch phng sai ANOVA 7. Hi quy tng quan 8. Kim nh phi tham s 9. L thuyt quyt nh1. 2. 3.

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Nhp s liu vo Excel

Con ngi Tm nhn mi

OBS 1 2 3 4 5 6 7 8 9 10

Y_PT 0 1 0 0 12 0 0 7 0 0

Z1_MALE Z2_AGE Z3_NOYM Z4_CHILD Z8_SATISFACTION 0 22 4 1 4 1 22 0.125 0 5 0 18 10 0 5 1 22 0.75 0 3 0 42 15 1 2 0 37 15 1 4 1 52 15 1 4 0 27 1.5 0 5 1 27 4 0 4 0 27 1.5 1 2

S dng file Excel: Business Statistics/ Resources/Learning-by-Doing/ Affair.xls OBS = S th t ca ngi c phng vn Y-PT = S ln quan h tnh dc ngoi hn nhn trong nm Z1_MALE = 1 nu l nam, 0 nu l n Z2_AGE = Tui Z3_NOYM = S nm kt hn Z4_CHILD = 1 nu c con, 0 nu cha c con Z8_SATISFACTION = Mc tha mn v hn nhn, thang Likert 1-5 Ghi ch : Bin s theo ct, quan st ghi theo hng5/12/2009 Nguyn Duy Tm _ IDR 3

To biu nhp liu (Form)

Con ngi Tm nhn mi

Trn mt trang bng tnh mi (New worksheet) To dng tiu (bin s) dng 1. Qut khi dng tiu , ri vo Data/ FormNguyn Duy Tm _ IDR 4

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To biu nhp liu (Form)

Con ngi Tm nhn mi

V chng ta khng nh ngha chnh xc s dng ca bng tnh, nn Excel c hi nh bng giao din trn. n gin l chn OK.Nguyn Duy Tm _ IDR 5

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Bn ghi cho ngi th nht

Con ngi Tm nhn mi

Nhp cho ngi th nht Bng s liu iu tra ca ngi ny nh sau OBS =1 Ngi th nht Y-PT =0 Cha ngoi tnh Z1_MALE =0 N Z2_AGE = 22 22 tui Z3_NOYM =4 Kt hn c 4 nm Z4_CHILD =1 c con Z8_SATISFACTION = 4 Hi lng v cuc hn nhn ca mnh

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Bn ghi cho ngi th nht

Con ngi Tm nhn mi

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Bn ghi cho ngi th hai

Con ngi Tm nhn mi

T Form nhp liu, click New nhp mt bn ghi (record) hay quan st (observation) mi. Bng s liu iu tra ca ngi th hai nh sau OBS =2 Ngi th hai Y-PT =1 ngoi tnh Z1_MALE =1 Nam Z2_AGE = 22 22 tui Z3_NOYM = 0.125 Kt hn c 1.5 thng (1.5/12) Z4_CHILD =0 Cha c con Z8_SATISFACTION = 5 Rt hi lng v cuc hn nhn ca mnh

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Bn ghi cho ngi th hai

Con ngi Tm nhn mi

Lm tng t cho n ngi th 10 slide 3.5/12/2009 Nguyn Duy Tm _ IDR 9

Con ngi Tm nhn mi

Mng th t

Chn bin Z2_AGE Sp xp thnh mng th t t nh n ln Qut khi ton b s liu, k c dng tn bin. Data/ Sort

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Giao din Sort

Con ngi Tm nhn mi

OBS

Z2_AGE 3 18 1 22 2 22 4 22 8 27 9 27 10 27 6 Kt qu 37 5 42 7 52

Chn Sort by: Z2_AGE Chn Asending: Sp xp theo th t tng dnNguyn Duy Tm _ IDR 11

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1. THNG K D LiU DNG BNG

Con ngi Tm nhn mi

Yu cu ca ni dung: Lp bng thng k cho cc bin thuc tnh v thuc lng. i vi bin t biu hin: mi biu hin 1 phn t i vi bin nhiu biu hin: tin hnh phn t li (Lp Bin) Cng c trn excel: Dng lnh =FREQUENCY[ (data_array, bins_array)]

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Con ngi Tm nhn mi

Quy trnh dng lnh FREQUENCY i vi bin c t biu hin B1: Lp ct cc biu hin (ct BIN): l gi tr cc biu hin B2: Chn vng d liu bng thng k, lp lnh Frequency C php: = FREQUENCY(data_array, bins_array) Data_array: D liu cn lp bng Bins_array: cc biu hin

Ch : Vi cc lnh thng thng, sau khi lp lnh, ch cn ENTER, nhng vi lnh FREQUENCY, ta cn g t hp fm [ctrl+shift+enter] V d: lp bng thng k cho tnh trng hn nhn [Marital]Nguyn Duy Tm _ IDR 13

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Con ngi Tm nhn mi

Quy trnh dng lnh FREQUENCY i vi bin c nhiu biu hin: B1: Cn lp cc [gii hn di] v [gii hn trn] ca mi phn t. B2: Lp ct Bin ch gm cc s gii hn trn ca mi phn t. V d bin [trnh hc vn]_edu B3: dng lnh FREQUENCY lp bng. Bi tp: lp bng tn s theo trnh hc vn, tui v trnh

kt hn. Ch : phn t do sinh vin t phn, c th phn t u hoc khng u5/12/2009 Nguyn Duy Tm _ IDR 14

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Con ngi Tm nhn mi

Biu tn s-Th tc Data AnalysisDng th tc Data Analysis trong th vin hm Add-Ins ca Excel Kim tra xem c th tc Data Analysis trong Tools hay cha? Tools/ Add-Ins/ Check vo Analysis ToolPak/ OK

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Biu tn s-Th tc Data Analysis

Con ngi Tm nhn mi

Tools/ Data Analysis/ Histogram

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Con Biu tn s-Th tc Data ngi Tm nhn mi Analysis

Input Range: Qut khi s liu, nh c c tn bin Bin Range: Qut bin khi bin trn ca biu tn s, nh c c tn Labels: Khai bo c dng u tin l tn bin Chn Output range: u tin cha kt qu Khai bo cc kt qu cn nhn: Pareto, Cumulative Percentage, Chart OutputNguyn Duy Tm _ IDR 17

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Con Biu tn s-Th tc Data ngi Tm nhn mi Analysis

BIN Frequency 20 1 30 6 40 1 50 1 60 1 More 0

Cumulative % BIN Frequency 10.00% 30 6 70.00% 20 1 80.00% 40 1 90.00% 50 1 100.00% 60 1 100.00% More 0

Cumulative % 60.00% 70.00% 80.00% 90.00% 100.00% 100.00%

Bng tn s, tn sut tch ly v phn phi Pareto

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Con Biu tn s-Th tc Data ngi Tm nhn mi AnalysisHistogram7 120.00%

6

100.00%

5 80.00% 4 60.00% 3 40.00% 2 Frequency Cumulative %

Frequency

1

20.00%

0 30 20 40 BIN 50 60 More

0.00%

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Biu Pareto19

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Con ngi Tm nhn mi

2. THNG K D LiU DNG TH

Cc dng th: 1. Hnh thanh : 2. Hnh trn, (bnh) : 3. ng gp khc : 4. Phn tn :

Column, Bar, Pie Line Scatter

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Con ngi Tm nhn mi

2. THNG K D LiU DNG TH

QUY TRNH V TH

TH HNH TRNTns

B1: chn vng d liu B2: chn biu tng th [chart wizart] hoc insert/chart B3: Chn cc hiu chnh tng ng

Rtkhng hi lng

1% 5%49%

12%

Khnghi lngBnh thng

33%Hilng Rthi lng

th hnh trn thng dng tn sut (%) hin th5/12/2009 Nguyn Duy Tm _ IDR 21

Con ngi Tm nhn mi

2. THNG K D LiU DNG TH TH HNH THANH [COLUMN] TH HNH THANH [BAR]

Tn thuc tnh di

Tn thuc tnh ngn5/12/2009 Nguyn Duy Tm _ IDR 22

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TH NG GP KHC _ LINE5/12/2009 Nguyn Duy Tm _ IDR 23

th Line: thng dng cho trng hp d liu theo di qua thi gian

ch s CPI180 160 140 120 100 80 60 40 20 0Jan-95 Jan-96 Jan-02 Jan-03 Jan-04 Jan-05Jan-97 Jan-98 Jan-99 Jan-00 Jan-01

Bng tm tt-Pivot Table

Con ngi Tm nhn mi

Data/ Pivot TableNguyn Duy Tm _ IDR 24

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Con ngi Tm nhn mi

Qut khi d liu cn tnh ton, k c tn bin, s c xem l tn trng(Field)

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Con ngi Tm nhn mi

Nn chn trang bng tnh miNguyn Duy Tm _ IDR 26

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Con ngi Tm nhn mi

Ko v nh (Drag and Drop) Z8_SATISFACTION vo Row Fields v Data ItemsNguyn Duy Tm _ IDR 27

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Con ngi Tm nhn mi

Nhp p vo A3 ( giao gia Row Fields v Column Fields) v chn Count of Z8_SATISFACTION.u im: c th tnh Tng, tn s v nhiu lnh khcNguyn Duy Tm _ IDR 28

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Pivot Table vi 2 bin phn loiCount of Z8_SATISFACTION Z8_SATISFACTION 1 2 3 4 5 Grand Total

Con ngi Tm nhn mi

Z1_MALE 0 11 35 46 93 130 315 1 5 31 47 101 102 286 Grand Total 16 66 93 194 232 601

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Pivot Table vi 2 bin phn loi

Con ngi Tm nhn mi

Click vo A3, ko v th trng Z1_MALE vo Column Fields.u im: lp bng tn s cho cho nhiu bin.Nguyn Duy Tm _ IDR 30

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Pivot Table vi 3 bin phn loi

Con ngi Tm nhn mi

Ko v th Z4_Child vo Page Fields

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Con ngi Tm nhn mi

Mt s yu cu

Dng cng c Pivot table: 1. Lp bng tng s con ca cc h gia nh c 1,2,,n con c th. 2. Lp bng tng s anh,ch em trong nh ng vi tng loi gia nh c th. 3. Lp bng tn s cho bin Marital, v biu v cho bit loi tnh trng hn nhn no chim a s 4. Lp bng tn s cho bin marita (column) v bin sex (row). V biu v cho bit gii tnh no ng vi tnh trng hn nhn no chim a s. V biu tng ng. 5. Lp bng tn s gia hai bin marital (column) v wrkstat (row). 6. Lp bng tn s gia hai bin marital (column) v wrkstat (row) v .

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Con ngi Tm nhn mi

Thng k d liu bng cc i lng thng k m t

CH TIU TP TRUNG

CH TIU PHN TN

Trung bnh : average =average(data) Trung v : Median =median(data) Mode : Mode =mode(data) T phn v : quartile =quartile(data,s phn v) (1: Q1; 2:Q2; 3:Q3)

Phng sai =var(data) lch chun =stdev(data)

: var : stdev

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Con ngi Tm nhn mi

Thng k d liu bng cc i lng thng k m tMT S LNH C TRONG EXCEL 2007 Tnh tng tha iu kin nng cao. =sumifs(vng tnh tng, vng K1, K1, vng K2, K2) m tha iu kin nng cao. =countifs(vng K1, K1,vng K2, K2,)

MT S LNH KHC

Tnh tng tho iu kin =sumif(vng K, K, Vng tnh tng) m tha iu kin =countif(vng K,K)

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Con ngi Tm nhn mi

Thng k d liu bng cc i lng thng k m tMT S LNH C TRONG EXCEL 2007

BI TP (AFFAIR)1.

Trung bnh tha iu kin =averageif(vng K, K, Vng tnh mean) =averageifs(vng tnh mean,vng K1, K1, Vng K2, K2)

2.

3.

Tnh gi tr trung bnh, trung v, mode, t phn v, phng sai, lch chun cho cc bin: Z2_age, Z4_child, Z6_edu. Nu ngha ca cc s trn. Tnh tng s con ca nhng ngi c tui di 30. hoc ca nhng ngi hi lng v tnh trng hn nhn. m nhng ngi c 1 con

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Con ngi Tm nhn mi

Thng k d liu bng cc i lng thng k m tBI TP (THUC HANH EXCEL)1.

BI TP (THUC HANH EXCEL)1.

2.

m nhng ngi lm vic ton thi gian trong mu kho st m nhng ngi lp gia nh, cha lp gia nh

2.

Tnh tng s anh/ch/em ca nhng ngi l d, ly thn. Tnh tng s con ca nhng ngi l n gii.

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Tnh tr thng k bng th tc Data Analysis Tools/ Data Analysis/ Descriptive Statistics

Con ngi Tm nhn mi

Nhp s liu v cc ty chn vo giao dinNguyn Duy Tm _ IDR 37

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Tnh tr thng k bng th tc Data Analysis Tools/ Data Analysis/ Descriptive StatisticsY_PT Z1_MALE Z2_AGE Mean 1.46 Standard Error 0.13 Median 0.00 Mode 0.00 Standard Deviation 3.30 Sample Variance 10.88 Kurtosis 4.26 Skewness 2.35 Range 12 Minimum 0 Maximum 12 Sum 875 Count 601 0.48 0.02 0.00 0.00 0.50 0.25 -2.00 0.10 1 0 1 286 601 32.49 0.38 32.00 27.00 9.29 86.28 0.23 0.89 39.5 17.5 57 19525 601 Z3_NOYM Z4_CHILD Z8_SATISFACTION Z5_RELIGIOUS Z6_EDU 8.18 0.23 7.00 15.00 5.57 31.04 -1.57 0.08 14.875 0.125 15 4914.795 601 0.72 0.02 1.00 1.00 0.45 0.20 -1.09 -0.96 1 0 1 430 601 3.93 0.04 4.00 5.00 1.10 1.22 -0.20 -0.84 4 1 5 2363 601 3.12 0.05 3.00 4.00 1.17 1.36 -1.01 -0.09 4 1 5 1873 601 16.17 0.10 16.00 14.00 2.40 5.77 -0.30 -0.25 11 9 20 9716 601

Con ngi Tm nhn mi

Z7_OCCUPATION 4.19 0.07 5.00 5.00 1.82 3.31 -0.78 -0.74 6 1 7 2521 601

Kt qu sau khi hiu chnh. Bi tp: Tnh cc ch tiu thng k m t bng cng c DATA ANALYSIS cho cc bin: agewed sibs childs age educ trong bi tp thc hnh excelNguyn Duy Tm _ IDR 38

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Con ngi Tm nhn mi

H S TNG QUAN

i tng bin p dng: bin nh lng (scale) hoc bin thuc thang o th bc (ordinal), bin thuc thang o khong (interval). Ch : i vi thang o nh danh (norminal): nhng ch s tnh ton khng c ngha thng k. Cng thc lnh: tnh rxy =correl(data_X, data_Y) ngha: o lng v mc quan h tuyn tnh gia hai bin X v Y -1 < = rxy < 0 : X v Y nghch bin 0< rxy P(1-a/2)= 0.975 Tra Za/2 = 1.96 Tnh trung bnh = 32.49 c lng khang tin cy 95%: (31.77; 33.21)Nguyn Duy Tm _ IDR

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C LNG KHONG TN Con ngiCHO mi CY Tm nhn GI TR TRUNG BNH (CHA BiT )

X ta / 2,n1

Chn a = 0.05 =>P(1-a/2)= 0.975 Tra ta/2 = 1.964 Tnh trung bnh = 32.49 v lch chun mu =9.29 c lng khang tin cy 95%: (31.74; 33.23)Nguyn Duy Tm _ IDR

S S X ta / 2,n1 n n

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Con ngi Tm nhn mi C LNG KHONG TN CY CHO GI TR TRUNG BNH (CHA BiT )_TH TC DATA ANALYSIS

Tools/ Data Analysis/ Descriptive Statistics Chn Summary Statistics v Confidence Level for Mean5/12/2009 Nguyn Duy Tm _ IDR 57

C LNG KHONG TN CY CHO GI TR TRUNG Con ngi Tm nhn mi BNH (CHA BiT )_TH TC DATA ANALYSIS

X ta / 2,n1

S S X ta / 2,n1 n n

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Cn di = Mean Confidence Level (95%) Cn trn = Mean + Confidence Level (95%)Nguyn Duy Tm _ IDR 58

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Con ngi Tm nhn mi

Bi tp c lngBI TP THUC HANH EXCEL1.

BI TP AFFAIR1.

c lng tui bnh qun (age) ca nhng ngi c kho st.

2. 3.

c lng tui bnh qun (age) ca nhng ngi c kho st c lng tui bnh qun kt hn (agewed). c lng trnh hc vn (educ) bnh qun ca nhng ngi c kho st.

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Kim nh 1 ui (Bit s)

Ho: S nm hc trung bnh ca ngi M ti a l 15 nm

Con ngi Tm nhn mi

Nhc li ng dn hm thng k: fx/ Statistical/ Average5/12/2009 Nguyn Duy Tm _ IDR 60

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Kim nh 1 ui (Bit s)

Con ngi Tm nhn mi


Gi tr Z = 11.44 nm min bc b =>C bng chng thng k cho thy s nm hc trung bnh ca ngi M ln hn 15 nm.5/12/2009 Nguyn Duy Tm _ IDR 61

Kim nh 1 ui (Khng bit s)


Con ngi Tm nhn mi

Lu : Hm TINV ng vi tra t hai ui nn khi tra t mt ui cn tra ng vi 2a.5/12/2009 Nguyn Duy Tm _ IDR 62

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Kim nh 1 ui (Khng bit s)

Con ngi Tm nhn mi


V tr thng k t = 1.70 nm min bc b nn chng ta bc b Ho. Vy s nm hc trung bnh ca ngi M cao hn 16.5/12/2009 Nguyn Duy Tm _ IDR 63

Kim nh 2 ui (Bit s)

Ho: S nm hc trung bnh ca ngi M l 16 nm

Con ngi Tm nhn mi

Hm NORMINV tr v gi tr Z ng vi xc sut tch ly nn phi nhp tham s l (1-a/2)5/12/2009 Nguyn Duy Tm _ IDR 64

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Kim nh 2 ui (Bit s)

Con ngi Tm nhn mi


Hm NORMINV tr v gi tr Z ng vi xc sut tch ly nn phi nhp tham s l (1-a/2) V tr thng k Z = 1.63 nm trong min chp nhn nn ta khng th bc b Ho.5/12/2009 Nguyn Duy Tm _ IDR 65

Kim nh 2 ui (Cha bit s)


Con ngi Tm nhn mi

Hm TINV(a, n-1)5/12/2009 Nguyn Duy Tm _ IDR 66

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Kim nh 2 ui (Cha bit s)Z6_EDU 9 16 14 17 14 14 18 17 20 17 Trung bnh lch chun = C mu n= Sai s chun = a= t a/ 2 = Ho: = H1 Tr thng k t= 16.17 2.40 601 0.10 0.05 1.964 16 16 1.70

Con ngi Tm nhn mi


V tr thng k t = 1.70 nm trong min chp nhn nn ta khng th bc b Ho.5/12/2009 Nguyn Duy Tm _ IDR 67

Con ngi Tm nhn mi

Bi tp kim nh

BI TP AFFAIR1.

BTP THC HNH EXCEL1.

2.

C gi thit cho rng, tui (age) bnh qun ca nhng ngi c kho st l di 30. Bn hy kim nh gi thit ny vi mc ngha =5%. C gi thit cho rng, tui (age) bnh qun ca nhng ngi c kho st l 33. Theo bn, gi thit ny ng hay sai? (=10%)

2.

3.

C gi thit cho rng, tui (age) bnh qun ca nhng ngi c kho st l di 40. Bn hy kim nh gi thit ny=5%. C gi thit cho rng, tui (age) bnh qun ca nhng ngi c kho st l 46. Theo bn, ng hay sai =3%? C gi thit cho rng, tui (agewed) bnh qun ca nhng ngi c kho st l di 40. Bn hy kim nh gi thit ny =4%.

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Con )-Gi tr p Kim nh 2 ui (Bit v Cha bitngi Tm nhn mi


ZTEST(Array, x, sigma) vi Array: S liu cn kim nh x: Gi tr ca pht biu Ho, Sigma: Nhp nu bit hoc trng nu khng bit.5/12/2009 Nguyn Duy Tm _ IDR 69

Kim nh 2 ui (Bit v Cha bit )-Gi tr pHo: S nm hc trung bnh ca ngi M l 16 nm

Con ngi Tm nhn mi

P_Value = 2*Min(ZTEST, 1-ZTEST) P_Value = 0.09> a = 0.05 => Khng th bc b Ho.

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Kim nh s khc bit v trung bnh ca hai tng th-Bit lch chun Affair.xls trang EduOBS MALE 1 2 3 4 5 0 0 0 0 0 EDU(FEMALE) 9 9 9 9 12 OBS MALE 1 2 3 4 5 1 1 1 1 1

Con ngi Tm nhn mi

EDU(MALE) EDU(FEMALE) EDU(MALE) 9 Trung bnh 15.26 17.17 9 lch chun 2.02 2.39 9 S quan st 315 286 12 12

Ho: Khng c s khc bit v hc vn trung bnh ca hai gii Kt qu kho st cho thy hc vn trung bnh ca nam nhnh hn ca n nhng lch chun cao hn. Kim nh Ho bng th tc Tools | Data Analysis | z-test: Two Sample for Means

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Con ngi ca hai Kim nh s khc bit v trung bnhTm nhn mi tng th-Bit lch chun

Tools | Data Analysis | z-test: Two Sample for Means5/12/2009 Nguyn Duy Tm _ IDR 72

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Con ngi Tm nhn mi Kim nh s khc bit v trung bnh ca hai tng th-Bit lch chun

Kt qu kim nh: Bc b Ho5/12/2009 Nguyn Duy Tm _ IDR 73

Con ngi Tm nhn mi Kim nh s khc bit v trung bnh ca hai tng th-Cha bit lch chun

Ho: Khng c s khc bit v hc vn trung bnh ca hai gii Tools | Data Analysis | t-Test: Two Sample Assuming Equal Variances5/12/2009 Nguyn Duy Tm _ IDR 74

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Con ngi Tm nhn mi Kim nh s khc bit v trung bnh ca hai tng th-Cha bit lch chun

Ho: Khng c s khc bit v hc vn trung bnh ca hai gii Tools | Data Analysis | t-Test: Two Sample Assuming Equal Variances Kt qu: Bc b Ho5/12/2009 Nguyn Duy Tm _ IDR 75

Con ngi Tm nhn mi

Bi tp kim nh mc lng trung bnh theo gii tnh

1.

2.

C kin cho rng mc lng trung bnh theo gii tnh gia nam v n l nh nhau. Vi s liu ca bi tp Tien luong khoi diem theo gioi tinh nam - nu.xls, bn hy kim nh gi thit trn. C gi thit cho rng, vic ci tin phn mm lm vic hin ti khng c hiu qu. Bng d liu bi tp hieu qua software.xls, bn hy kim nh hiu qu ca phn mm mi v c.

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Con ngi Tm nhn mi Kim nh F cho s khc bit v phng sai ca hai tng th

Ho: Khng c s khc bit v phng sai ca hc vn trn hai gii Tools | Data Analysis | F-Test: Two-Sample for Variances5/12/2009 Nguyn Duy Tm _ IDR 77

Con ngi Tm nhn mi Kim nh F cho s khc bit v phng sai ca hai tng th

Ho: Khng c s khc bit v phng sai ca hc vn trn hai gii Kt qu: Bc b Ho5/12/2009 Nguyn Duy Tm _ IDR 78

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Con ngi Tm nhn mi Kim nh mu cp: V v chng c cm nhn khc bit v hnh phc khng? Affair.xls/ Satisfaction

Ho: V v chng tha mn v hn nhn nh nhau. Tools | Data Analysis | t-test: Paired Two Sample for Means5/12/2009 Nguyn Duy Tm _ IDR 79

Kim nh mu cp: V v chng Con ngi Tm nhn mi c cm nhn khc bit v hnh phc khng?

Ho: V v chng tha mn v hn nhn nh nhau. Kt qu: Chp nhn Ho.5/12/2009 Nguyn Duy Tm _ IDR 80

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Con ngi Tm nhn mi

Bi tp kim nh cp

C gi nh cho rng, hiu qu ca mt phng php qung co c tin hnh cho nhiu cng ty khc nhau hin ti khng c hiu qu. Bng s liu ca bi tp truoc - sau quang cao ve doanh thu.xls, anh ch hy kim nh gi thit trn

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Nguyn Duy Tm _ IDR

81

Con ngi Tm nhn mi HM TTEST-Kim nh s khc bit

fx/ Statistical/ TTEST Type: 1 cho mu cp, 2 cho phng sai bng nhau, 3 cho phng sai khc nhauNguyn Duy Tm _ IDR 82

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Con ngi Tm v hn ANOVA: V v chng c c mc hi lngnhn mi nhn trung bnh khc nhau khng?

Ho: V v chng tha mn v hn nhn nh nhau. Tools/ Data Analysis/ ANOVA-Single Factor5/12/2009 Nguyn Duy Tm _ IDR 83

Con ngi Tm nhn ANOVA: Nam v n c c mc hi mi lng v hn nhn khc nhau khng?Anova: Single Factor SUMMARY Groups WIFE HUSBAND ANOVA Source of Variation Between Groups Within Groups Total

Count Sum Average Variance 250 999 4.00 1.30 250 984 3.94 1.06

SS 0.45 586 586

df 1.00 498 499

MS 0.45 1.18

F 0.38

P-value F crit 0.54 3.86

Ho: Hai gii tha mn v hn nhn trung bnh nh nhau. Kt qu: Chp nhn Ho

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84

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Con ngi Tm nhn ANOVA mt nhn t-V d chng 8 Worksheet in mi Chapter8(V)

So snh nng sut ca 3 my Ho: Nng sut ca 3 my l nh nhauNguyn Duy Tm _ IDR 85

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ANOVA mt nhn t-V dCon ngi Tm nhn mi chng 8 Anova: Single FactorSUMMARY Groups Machine 1 Machine 2 Machine 3 Count 5 5 5 Sum Average Variance 124.65 24.93 1.06 113.05 22.61 0.78 102.95 20.59 0.92

ANOVA Source of Variation Between Groups Within Groups Total

SS 47.16 11.05 58.22

df 2 12 14

MS 23.58 0.92

F P-value F crit 25.60 0.00 3.89

Ho: Nng sut ca 3 my l nh nhau Kt qu kim nh: Bc b Ho5/12/2009 Nguyn Duy Tm _ IDR 86

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Th tc Tukey-Kramer

Con ngi Tm nhn mi

Tools/ Lumenaut Statistics/ Tukey-Kramer Test Lumenaut l mt phn mm Add-Ins min ph, chy trn nn Excel.5/12/2009 Nguyn Duy Tm _ IDR 87

Con ngi Tm nhn mi

Th tc Tukey-Kramer

Tools/ Lumenaut Statistics/ Tukey-Kramer TestNguyn Duy Tm _ IDR 88

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Th tc Tukey-KramerTukey-Kramer Test

Con ngi Tm nhn mi

v 9

k 3

Critical Value Q 3.948

MS within 0.921

MSD Values Stack Machine 1 Machine 2 Machine 1 1.695 Machine 2 2.320 Machine 3 4.340 2.020

Meani-Meanj

Machine 3 1.695 1.695

If Meani-Meanj > MSD value then pair is significantly different at the 5% level (1 Tailed) Significant pair values are in bold and underlined in above Table

Tools/ Lumenaut Statistics/ Tukey-Kramer TestNguyn Duy Tm _ IDR 89

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Tm h s chn v dc

Con ngi Tm nhn mi

H s chn: fx/ Statistical/ INTERCEPT dc: fx/ Statistical/ SLOPENguyn Duy Tm _ IDR 90

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Tm h s chn v dc

Con ngi Tm nhn mi

H s chn: fx/ Statistical/ INTERCEPT dc: fx/ Statistical/ SLOPENguyn Duy Tm _ IDR 91

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V ng xu hng trong Chart

Con ngi Tm nhn mi

Click phi/ Add Trendline/Nguyn Duy Tm _ IDR 92

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V ng xu hng trong Chart

Con ngi Tm nhn mi

Type: Linear Options: Display Equation on chartNguyn Duy Tm _ IDR 93

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Con ngi Tm nhn mi

V ng xu hng trong Chart12,000

10,000

y = 1.5x + 1636.4 R2 = 0.9

8,000

Sales

6,000

Sales Linear (Sales)

4,000

2,000

0 0 1,000 2,000 3,000 Footage 4,000 5,000 6,000

Kt quNguyn Duy Tm _ IDR 94

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Th tc REGRESSION

Con ngi Tm nhn mi

Tools/ Data Analysis/ REGRESSIONNguyn Duy Tm _ IDR 95

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KT QUSUMMARY OUTPUT Regression Statistics Multiple R 0.97 R Square 0.94 Adjusted R Square 0.93 Standard Error 611.75 Observations 7 ANOVA df Regression Residual Total 1 5 6 SS 30,380,456 1,871,200 32,251,656 MS 30380456 374240

Con ngi Tm nhn mi

F Significance F 81.18 0.00

Intercept Footage

Coefficients Standard Error 1,636.41 451.50 1.49 0.16

t Stat P-value 3.62 0.02 9.01 0.00

Lower 95% Upper 95% 475.81 2,797.02 1.06 1.91

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96

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T bng kt xut ca ExcelResiduals12000

Con ngi Tm nhn mi

Predicted Sales and Residuals

10000 8000 6000 4000 2000 0 -2000

Predicted Sales Residuals

0

2

4 Observations

6

8

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Phn d theo bin c lp

Con ngi Tm nhn mi

Footage Residual Plot 1000 800 600 400 200 0 -200 0 -400 -600 -800 Footage 1,000 2,000 3,000 4,000 5,000 6,000

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Residuals

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Real and Fitted ValuesFootage Line Fit Plot 12,000 y = 1.4866x + 1636.4 10,000 8,000 R =12

Con ngi Tm nhn mi

Sales

6,000 4,000 2,000 0 0 1,000 2,000 3,000 Footage5/12/2009 Nguyn Duy Tm _ IDR

Sales Predicted Sales Linear (Predicted Sales)4,000 5,000 6,000

99

Con ngi Tm nhn Tools/ Data Analysis/ Regression mi

Hi quy n: Oil theo TempL Tn Lut 100

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Hi quy n: Oil theo TempSUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA df Regression Residual Total 1 13 14 SS 178624 57511 236135 MS 178624 4424

Con ngi Tm nhn mi

0.87 0.76 0.74 66.51 15

F

Significance F 40 0.00

Intercept Temp

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% 436.43823 38.63970893 11.29507 4.3E-08 352.962214 519.914246 -5.4622077 0.859608768 -6.3543 2.52E-05 -7.3192795 -3.6051359

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L Tn Lut

101

Hi quy n: Oil theo InsulationSUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA df Regression Residual Total 1 13 14 SS 51,076 185,059 236,135 MS 51,076 14,235

Con ngi Tm nhn mi

0.47 0.22 0.16 119 15

F

Significance F 3.59 0.08

Intercept Insulation

Coefficients Standard Error 345.38 74.69 -20.35 10.74

t Stat P-value Lower 95% Upper 95% 4.62 0.00 184.02 506.74 -1.89 0.08 -43.56 2.86

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L Tn Lut

102

51

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Hi quy bi: Oil theo Temp v Insulation Qut Knowns X: c Temp v InsulationSUMMARY OUTPUT Regression Statistics Multiple R 0.98 R Square 0.97 Adjusted R Square 0.96 Standard Error 26.01 Observations 15 ANOVA df Regression Residual Total 2 12 14 SS 228015 8121 236135 MS 114007 677 F

Con ngi Tm nhn mi

Significance F 168 0.00

Intercept Temp Insulation

Coefficients Standard Error 562.15 21.09 -5.44 0.34 -20.01 2.34

t Stat P-value Lower 95% Upper 95% 26.65 0.00 516.19 608.11 -16.17 0.00 -6.17 -4.70 -8.54 0.00 -25.12 -14.91

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L Tn Lut

103

Bin Insulation c ci thin m hnh t Oil = f(Temp) khng?

Con ngi Tm nhn mi

Kt qu tnh ton cho Fc = 73

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L Tn Lut

104

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Tra gi tr ti hn ca F: FINV

Con ngi Tm nhn mi

Kt qu tnh ton F* = 4.75 F =73 > F*: 4.75 Kt lun: Insulation lm tng mc gii thch ca m hnh.5/12/2009 L Tn Lut 105

Hi quy bc hai: Chun b s liuTm nhn mi Con ngi Temp2=Tem^2Oil (Gal) Temp Temp2 275.30 40 1600 363.80 27 729 164.30 40 1600 40.80 73 5329 94.30 64 4096 230.90 34 1156 366.70 9 81 300.60 8 64 237.80 23 529 121.40 63 3969 31.40 65 4225 203.50 41 1681 441.10 21 441 323.00 38 1444 52.50 58 3364

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L Tn Lut

106

53

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Kt qu hi quySUMMARY OUTPUT Regression Statistics Multiple R 0.88 R Square 0.78 Adjusted R Square 0.74 Standard Error 65.71 Observations 15 ANOVA df Regression Residual Total 2 12 14 SS 184,324 51,811 236,135 MS 92,162 4,318

Con ngi Tm nhn mi

F 21

Significance F 0.00

Intercept Temp Temp2

Coefficients Standard Error 372.33 67.60 -1.26 3.75 -0.05 0.05

t Stat P-value 5.51 0.00 -0.34 0.74 -1.15 0.27

Lower 95% Upper 95% 225.04 519.62 -9.44 6.91 -0.15 0.05

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Hi quy vi bin gi

Con ngi Tm nhn mi

TC = Tng chi ph sn xut Q = Tng sn lng CN = 1 cho cc qu thay i cng ngh, 0 cho cc qu trc khi thay i cng ngh. TCN = 0 cho cc qu thay i cng ngh, 1 cho cc qu trc khi thay i cng ngh.

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L Tn Lut

108

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Sai lm -> a cng tuynCon ngi Tm nhn mi hon hoSUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA df Regression Residual Total 3 13 16 SS 291,681 41,727 333,408 MS 97,227 3,210 F 45 Significance F 0.00 0.94 0.87 0.78 56.65 16

Intercept Q CN TCN

Coefficients Standard Error t Stat P-value 521.80 122.46 4.26 0.00 0.81 0.10 8.04 0.00 0.00 0.00 65,535.00 #NUM! 210.63 52.80 3.99 0.00

Lower 95% Upper 95% 257.24 786.35 0.59 1.03 0.00 0.00 96.55 324.70

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L Tn Lut

109

Hi quy vi bin giSUMMARY OUTPUT Regression Statistics Multiple R 0.94 R Square 0.87 Adjusted R Square 0.86 Standard Error 56.65 Observations 16 ANOVA df Regression Residual Total 2 13 15 SS 291,681 41,727 333,408 MS 145,841 3,210

Con ngi Tm nhn mi

F Significance F 45.44 1.36E-06

Intercept Q CN

Coefficients Standard Error 732.42 79.51 0.81 0.10 -210.63 52.80

t Stat P-value 9.21 0.00 8.04 0.00 -3.99 0.00

Lower 95% Upper 95% 560.65 904.20 0.59 1.03 -324.70 -96.55

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110

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Hi quy vi bin tng tc SUMMARY OUTPUT CNQ = CN*QRegression Statistics Multiple R 0.98 R Square 0.96 Adjusted R Square0.95 Standard Error 33.19 Observations 16 ANOVA df Regression Residual Total 3 12 15 SS 320190 13218 333408 MS 106730 1102

Con ngi Tm nhn mi

F Significance F 96.90 1.11913E-08

Intercept Q CN CNQ

Coefficients Standard Error 401.52 80.00 1.24 0.10 368.96 118.05 -0.64 0.13

t Stat P-value 5.02 0.00 11.98 0.00 3.13 0.01 -5.09 0.00

Lower 95% Upper 95% 227.21 575.83 1.02 1.47 111.75 626.17 -0.92 -0.37

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L Tn Lut

111

Con ngi Tm tc ngha ca bin gi v bin tng nhn mi

TC = 401 + 1.24*Q + 368*CN 0.64CNQ P (0.00) (0.00) (0.01) (0.00) 2 = 0.96 R Adjusted R2= 0.95 n= 16 Trc thay i cng ngh: CN=CNQ=0 TC = 401 + 1.24*Q Sau thay i cng ngh: CN=1, CNQ=Q TC = (401+368) + (1.24-0.68)*Q TC = 769 + 0.56*Q Vy thay i cng ngh lm nh ph tng nhng bin ph n v gim.

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L Tn Lut

112

56

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Con ngi Tm nhn Hi quy vi bin chuyn dng log-logmi M hnh tuyn tnh: Q=b1+b2*L+b3*KSUMMARY OUTPUT Regression Statistics Multiple R 0.99 R Square 0.99 Adjusted R Square 0.99 Standard Error 1,570.36 Observations 15 ANOVA df Regression Residual Total 2 12 14 SS MS 2686989117 1.34E+09 29592539.09 2466045 2716581656 F 545 Significance F 1.67092E-12

Intercept L K

Coefficients Standard Error -32,375.93 3,140.85 2.62 6.43 344.47 40.87

t Stat P-value Lower 95% Upper 95% -10.31 0.00 -39,219.24 -25,532.61 0.41 0.69 -11.39 16.62 8.43 0.00 255.43 433.51

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L Tn Lut

113

Chuyn dng log-log

Con ngi Tm nhn mi

Hm sn xut Cobb-Douglas Q = A*La*Kb (1) Khng th c lng trc tip hm (1) ln(Q) = ln(A) + a*ln(L) + b*ln(K) Y = b0 + b1*X1 + b2*X2 Vi b0 = ln(A); b1= a; b2=b; X1= ln(L); X2=ln(K) Chng ta chuyn v dng m hnh hi quy tuyn tnh thng thng

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L Tn Lut

114

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Chun b s liu log-log: Hm Con ngi Tm nhn mi ln(Number)lnQ 9.10 9.29 9.32 9.31 9.45 9.70 9.88 9.96 10.05 10.17 10.29 10.42 10.55 10.76 10.905/12/2009 L Tn Lut

lnL 5.64 5.65 5.67 5.93 5.93 6.00 6.17 6.32 6.42 6.54 6.67 6.70 6.74 6.77 6.91

lnK 4.79 4.81 4.83 4.86 4.88 4.90 4.93 4.99 5.04 5.10 5.18 5.24 5.33 5.40 5.48115

Kt qu hi quySUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA df Regression Residual Total 2 12 14 SS 4 0 5 MS 2 0

Con ngi Tm nhn mi

0.99 0.98 0.97 0.09 15

F 267

Significance F 1.13248E-10

Intercept lnL lnK

Coefficients Standard Error -0.38 0.78 0.67 0.17 1.22 0.34

t Stat P-value -0.49 0.63 3.85 0.00 3.56 0.00

Lower 95% Upper 95% -2.07 1.31 0.29 1.04 0.47 1.96

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L Tn Lut

116

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