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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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1. THNG K D LiU DNG BNG
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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1. THNG K D LiU DNG BNG
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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Bng tm tt-Pivot Table
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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Bng tm tt-Pivot Table
Con ngi Tm nhn mi
Nn chn trang bng tnh miNguyn Duy Tm _ IDR 26
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Bng tm tt-Pivot Table
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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Bng tm tt-Pivot Table
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
Ho: S nm hc trung bnh ca ngi M ti a l 15 nm
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)
Ho: S nm hc trung bnh ca ngi M ti a l 16 nm
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
Ho: S nm hc trung bnh ca ngi M ti a l 16 nm
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
Ho: S nm hc trung bnh ca ngi M l 16 nm
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)
Ho: S nm hc trung bnh ca ngi M l 16 nm
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
Ho: S nm hc trung bnh ca ngi M l 16 nm
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
Ho: S nm hc trung bnh ca ngi M l 16 nm
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
40
5/12/2009
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
5/12/2009
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
5/12/2009
41
5/12/2009
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
5/12/2009
Nguyn Duy Tm _ IDR
84
42
5/12/2009
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
5/12/2009
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
43
5/12/2009
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
5/12/2009
44
5/12/2009
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
5/12/2009
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
5/12/2009
45
5/12/2009
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
5/12/2009
V ng xu hng trong Chart
Con ngi Tm nhn mi
Click phi/ Add Trendline/Nguyn Duy Tm _ IDR 92
5/12/2009
46
5/12/2009
V ng xu hng trong Chart
Con ngi Tm nhn mi
Type: Linear Options: Display Equation on chartNguyn Duy Tm _ IDR 93
5/12/2009
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
5/12/2009
47
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Th tc REGRESSION
Con ngi Tm nhn mi
Tools/ Data Analysis/ REGRESSIONNguyn Duy Tm _ IDR 95
5/12/2009
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
5/12/2009
Nguyn Duy Tm _ IDR
96
48
5/12/2009
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
5/12/2009
Nguyn Duy Tm _ IDR
97
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
5/12/2009
Residuals
Nguyn Duy Tm _ IDR
98
49
5/12/2009
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
5/12/2009
50
5/12/2009
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
5/12/2009
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
5/12/2009
L Tn Lut
102
51
5/12/2009
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
5/12/2009
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
5/12/2009
L Tn Lut
104
52
5/12/2009
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
5/12/2009
L Tn Lut
106
53
5/12/2009
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
5/12/2009
L Tn Lut
107
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.
5/12/2009
L Tn Lut
108
54
5/12/2009
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
5/12/2009
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
5/12/2009
L Tn Lut
110
55
5/12/2009
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
5/12/2009
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.
5/12/2009
L Tn Lut
112
56
5/12/2009
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
5/12/2009
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
5/12/2009
L Tn Lut
114
57
5/12/2009
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
5/12/2009
L Tn Lut
116
58