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课程目录6 O2 i2 O \: ~
1 - Lauren's Intro Video / \ [6 V; p- d" F7 G! {
10 - Sampling Distribution Shape % c3 p% z9 U+ e3 ^; T' v
100 - Two-Tailed Critical Values 0.05 Solution ! X" J$ H" A6 `6 ~6 C/ ?) n
101 - Two-Tailed Test
7 i- F/ g; c* Q102 - Two-Tailed Test Solution
m0 A$ }" W# L" J1 `- Y/ m103 - Two-Tailed Probability
% t/ C% e j( M) V5 [104 - Two-Tailed Probability Solution
6 ]4 ^* Z; A: A N8 ]# m105 - Two-Tailed Critical Values 0.01 # C5 O B. F, Y G B
106 - Two-Tailed Critical Values 0.01 Solution ( l$ Y4 r6 C; x4 P2 h. ]: |( g
107 - Two-Tailed Critical Values 0.001
0 \3 G* V [% ~: X* c5 d: k108 - Two-Tailed Critical Values 0.001 Solution 7 a( I4 K( x1 l( b
109 - Hypotheses , C; Q% V+ a2 o' \, }
11 - Sampling Distribution Shape Solution $ s; |2 n5 ?" K7 G% M3 M" y
110 - Fail to Reject the Null 7 z! g7 g5 K3 A& J) c. U+ g
111 - Fail to Reject the Null Solution 6 w) M! ^. v' D0 S
112 - Evidence to Reject the Null
# I0 D& u: d; F6 Y113 - Evidence to Reject the Null Solution
. v$ s) }1 E5 Z: _; m) ?: P114 - Mean and SD 5 t, q( b7 ]# W0 `% P3 I+ E
115 - Mean and SD Solution ( h9 [4 _* k" n1 k
116 - Null Hypothesis
9 }0 J4 M9 O B* v, J6 `117 - Null Hypothesis Solution $ r0 t$ C1 `( Z3 j
118 - Alternative Hypothesis
6 b# ~( R9 p# f4 d2 H) g W+ u! m119 - Alternative Hypothesis Solution % Z& A; q, l$ I+ H/ p9 ]
12 - What Do You Get with a Good Klout Score_
7 b0 F E* G7 r6 B- b120 - One tailed or two tailed
5 L( G8 X7 c) T0 m121 - Conduct Hypothesis Test
^8 u6 O* C% J$ x, [, s& x122 - Conduct Hypothesis Test Solution
3 L6 C* b7 R/ T" W, U123 - Critical Values 0.05
n9 t2 p: l! Q' c124 - Critical Values 0.05 Solution $ F! N3 }( c$ W, ~
125 - Z-Score of Sample Mean
; [; I& \+ u$ u* } {2 j. @! h' }2 U126 - Z-Score of Sample Mean Solution $ l* H! \$ U1 A9 U& e" F
127 - Results of Hypothesis Test
4 b6 J2 y( M4 z* k$ K- q; b128 - Results of Hypothesis Test Solution
2 Y- {+ g4 Z0 m* ?# O7 \. {1 X2 y( H/ {129 - Increase Sample Size ( C8 L! q6 Y* r' ^* ?
13 - Location of Mean on Distribution . O3 z8 `& s: C
130 - Increase Sample Size Solution 0 h7 K' |- @* @) C4 j
131 - Reject or Fail to Reject
9 X0 t6 c/ o$ Q$ {( S132 - Reject or Fail to Reject Solution
0 x4 @5 |3 i4 m6 Y* _133 - Probability of Obtaining Mean
5 k6 C" |* Y+ D& x% _( u2 Z134 - Probability of Obtaining Mean Solution
7 @& `8 B/ ]+ L' F& x: y4 A135 - Decision Errors
+ C" b r( ]! ]8 _3 J136 - Decision Errors Solution
0 k. a6 O$ j9 E2 _# Z137 - Hot Beverage 9 V, ?( O7 ]/ S; g3 x! x: W
138 - Hot Beverage Solution : z V; @ @# H: R; z
139 - Raining
2 ^( {; a( D& L, z4 l14 - Location of Mean on Distribution Solution
% t3 P) |4 q' g. {140 - Raining Solution : r" t/ e- F- [+ I- ~
141 - What Happened_ " R8 ?& v6 A! |0 y
142 - What Happened_ Solution # p; \; W5 y; ^, ?( a
143 - What Happened_ 2 T( M u! ^- _! k& {9 L. ^
144 - What Happened_ Solution
( O; X' n7 C/ S# n* Q4 c- ]145 - Prone to Misinterpretations 8 a2 g6 B# Q# b% P0 s2 X
146 - To Finish This Lesson... $ |' a' F) z1 S
147 - Hypothesis Testing - z; B5 N, m, k \! G, M1 q% l! [. n
148 - Increase Engagement_
7 x4 \3 P% O }5 P; _) R/ b0 r149 - t-Distribution
/ @9 v# c! j& G) X& m: Q% |15 - Probability of Obtaining Mean 6 B+ b K/ d7 g4 ~
150 - t-Distribution Solution u, S* R) _- b i3 s- g
151 - Guinness + O! q% T% G2 M: X ~- p
152 - Degrees of Freedom
% W/ x. p4 q4 F; _! ?7 N8 T153 - Degrees of Freedom Solution
) l' c4 ], N0 k154 - DF - Choose n Numbers 5 f& D# s0 H# P
155 - DF - Choose n Numbers Solution
5 r# y8 @4 K- t$ u( @8 W156 - DF - Add to 10
) U7 C* R0 U+ g4 C y" S6 x2 T0 x0 e157 - DF - Add to 10 Solution % c2 q o# [, T$ W3 x
158 - DF - Marginal Totals ( e. w3 U8 ^* `( c& A, h* J( Y5 Z8 x
159 - DF - Marginal Totals Solution
' V2 T7 l: L7 ^* H16 - Probability of Obtaining Mean Solution
' `/ p; J3 E& ^, y. i, ^160 - DF - Sample SD
( P$ q8 ?5 d9 k# f/ G7 A/ P/ p161 - t-Table " i# z( _9 B) @2 O7 K
162 - One-Tailed t-Test $ Y' s) a& N" M9 U2 d
163 - One-Tailed t-Test Solution
: p6 \% @/ a+ `1 y @164 - Two-Tailed t-Test i0 u/ Y& H$ }) J1 c- O3 G5 r
165 - Two-Tailed t-Test Solution # B" W1 C/ a; H( _- @1 l* n
166 - Bounds of Area ! o* v, A9 p% c
167 - Bounds of Area Solution
' @% S5 l, K3 g% \) @1 ^9 Q0 U168 - Affect t-Statistic 5 q; z" W+ a$ H& Z' g) s) c
169 - Affect t-Statistic Solution
$ U; d$ T/ f* o \- j$ P17 - Does Low Probability = Causation_
3 C! `; H) _- K ~" G170 - One-Sample t-Test ( E4 V }; }2 {; N$ R
171 - Increase t ' [1 j" F; z: B
172 - Increase t Solution ( F/ p) v1 m% q9 Y
173 - Finches / ~7 V, J) v& A8 K0 Z
174 - Finches Solution 6 |4 H# u s4 L g
175 - Finches - n and DF
9 Z! U( E# H1 Q. @7 p' j176 - Finches - n and DF Solution
! y* g. m% G7 x- v! L& {: Y: a177 - Finches - Mean and s # W/ i! T9 O$ r5 d, y3 O, j
178 - Finches - Mean and s Solution ( i5 K3 d; d J
179 - Finches - Find t-Statistic
3 C" d7 t: O/ n# s0 d6 k& r18 - Does Low Probability = Causation_ Solution
2 I. J) T9 R& m% v180 - Finches - Find t-Statistic Solution
2 d4 _ \, O5 P6 Y' F) m& d181 - Finches - Decision
) Z8 f9 E9 O. @+ [182 - Finches - Decision Solution
1 X! [4 T) E o8 N& d183 - P-Value ; Y% n+ Z5 u+ L" s% M
184 - P-Value Solution
( a) q3 ]/ R. X c1 r* J. I9 U185 - Visualize P-Value & B0 v2 }+ e+ E/ I- r6 K
186 - Visualize P-Value Solution
! X6 \" _6 l2 d& E9 @! V187 - Find P-Value
2 u! y. J, q3 v& k188 - Find P-Value Solution 7 a T# P; P! ]
189 - Rent - t-Critical Values 3 x) C! k- _0 m8 b ]
19 - Increase Sample Size 8 [; A( [( s/ {4 @- x% {
190 - Rent - t-Critical Values Solution / H$ O6 m% t, G" O4 z R
191 - Rent - t-Statistic 0 Y$ [6 d5 V4 n# D7 M, W
192 - Rent - t-Statistic Solution , ~( n* n& S' c- S# p1 `% d/ [9 b5 n
193 - Rent - Decision
, H/ T6 o7 R n' U! K194 - Rent - Decision Solution
4 a. U4 ~2 O9 D$ s5 B8 D( d195 - Rent - Cohen's d ; w5 J& Q4 O+ m2 c( j7 b
196 - Rent - Cohen's d Solution
% h% b* Y) N# }' Z5 m* l197 - Rent - CI ( ^, E# F* j4 y* _# `
198 - Rent - CI Solution ' }+ J L5 I7 N2 a; v
199 - Rent - Find CI
6 P" f) `: F1 E4 w2 - Intro ! ^8 b% L4 |7 [, c
20 - Increase Sample Size Solution
8 V6 D& M) g2 ~200 - Rent - Find CI Solution
{/ V [" p9 u7 y201 - Rent - Margin of Error 2 @( K6 S t7 B# \
202 - Rent - Margin of Error Solution ' r5 Y) _" f3 o r3 e, V
203 - Rent - Increase n $ B9 l0 m) u0 c4 y, o. W
204 - Rent - Increase n Solution
) m2 G% `' K0 h205 - Dependent Samples
( h. Z! w- _' m206 - Keyboards
( b$ g: G! q/ S8 R207 - Keyboards Solution
0 H# l- q1 l: [! c208 - Keyboards_ Point Estimate for Difference
4 j, p0 J; Z* U" u6 x; Y9 x3 V! D209 - Keyboards_ Point Estimate for Difference Solution
* t( P1 C8 E& R9 \' W" ]2 J R21 - Location of Mean
" U) R3 U* N- K0 ^9 }210 - Keyboards - SD of Differences
4 G. c, J' Q% e5 t2 j7 e211 - Keyboards - SD of Differences Solution $ _5 r' ]5 w; p* \4 D# a
212 - Keyboards - t-Statistic - t4 f% R6 a- n8 k
213 - Keyboards - t-Statistic Solution 5 l- H8 m$ q) J# b r/ d8 p
214 - Keyboards - t-Critical Values
# i3 K7 Z7 l% F( W+ c5 V3 t7 E215 - Keyboards - t-Critical Values Solution , F, m' z) G# g4 ]4 d/ p% n% i& \
216 - Keyboards - Decision
$ z8 Z2 D( n5 Z3 b+ ^, g s# U217 - Keyboards - Decision Solution 2 D' R# R* A. |
218 - Keyboards - Cohen's d
, q) t. a) q( L/ A5 L$ ^# H* ^5 T r. f: I219 - Keyboards - Cohen's d Solution
6 O- N) u8 Q- u( x22 - Location of Mean Solution
. C: x2 e+ Q% N4 _/ r220 - Keyboards - CI for Dependent Samples
" h" X2 N& ^+ Q' c- u4 ?4 {221 - Keyboards - CI for Dependent Samples Solution 1 B* n# s& U! v; s/ o
222 - Notation for Difference , Y1 [) @9 U3 \" X# I
223 - Types of Designs & G% q- J. C6 {+ J1 Z7 S: j
224 - Effect Size ' A, K" f" X \
225 - Everyday Meaning
[, j i a* Q& d5 p, a ]# T# G# G226 - Everyday Meaning Solution
# \ Y( L* R: v" i$ u227 - Types of Effect-Size Measures 5 D' M* _: [3 U: R
228 - Statistical Significance 7 l( @5 z' ?: Z: q
229 - Cohen's d 8 E( m: U$ R/ K
23 - Probability of Mean & O+ ?+ n$ t- t% i7 I
230 - r^2 ) ?' E3 ~/ n( S0 p* m Q
231 - Compute r^2 * M' |/ E4 w& x+ H7 e
232 - Compute r^2 Solution : j& h# ]* g- L0 ]- `
233 - Report Results , N% Z4 c* T9 k! @
234 - Report CI Results
9 d& A3 S$ [$ y* @8 n& W5 T7 N235 - Report CI Results 2
# a/ ^$ C) C$ v236 - Report Results Effect Size 5 U' n* f8 W$ {
237 - One-Sample t-Test : T$ |2 y) |+ j0 t+ y; a
238 - Mu - J" M( D9 N5 a+ i; H$ C* k& v
239 - Dependent Variable
8 ^% _' R/ } k8 ]5 r( d" A24 - Probability of Mean Solution
9 R( K o4 J+ }1 L5 m2 M240 - Dependent Variable Solution & m M& U: l1 S9 d! H3 ~" F
241 - Treatment
& G) P3 G$ ?3 Y- I' J# d242 - Treatment Solution 0 F- F( r$ Y" C+ u' d j# d- ]9 @
243 - Null Hypothesis & A. P+ q3 a1 n$ a7 E- Z
244 - Null Hypothesis Solution
6 ~. k0 \* J3 r* @245 - Alternative Hypothesis ; ^; d/ _+ E" h. J' ?
246 - Alternative Hypothesis Solution & m# {5 V1 w6 |. C
247 - Hypotheses
$ V% u5 D( G2 S& l( `1 d248 - Which-Tailed Test_
: w$ p6 J% g7 ?% d* F1 k, E1 m249 - Which-Tailed Test_ Solution
7 I4 q9 R ^ o) Z+ ?# L25 - Something Fun
& B* @- N9 Y5 I250 - Degrees of Freedom
?% r+ E2 B d2 }251 - Degrees of Freedom Solution
! n4 t) i( w# A) h& C252 - t-Critical
& }9 s7 q! W% ^253 - t-Critical Solution ; \, }5 w. d ], E- J
254 - SEM ; @' k! ^+ v# y% g. [& W- M) L* G
255 - SEM Solution
7 T Z+ G- C! @256 - Mean Difference * ]5 M; D$ A$ f# U4 ~: @. j
257 - Mean Difference Solution 7 F1 W1 F. f2 j
258 - t-Statistic ; R) q/ r' z) C* S
259 - t-Statistic Solution 8 ?5 {( T! p# e5 B) W' \
26 - Something Fun Solution
; n3 A# s3 j$ N. \260 - Critical Region
* o# a$ M* H/ g3 Q0 ~261 - Critical Region Solution & y) x% W( x G: S
262 - P-Value - M/ d0 d' \/ r+ \* J
263 - P-Value Solution
- m2 b% G# y$ E5 {& ^264 - Statistically Significant ( G$ ~3 B+ u1 x0 q
265 - Statistically Significant Solution
( n5 }9 M y$ l6 z8 M266 - Meaningful Results
" Z! |. p) h; {2 R. {# k6 P" B267 - Meaningful Results Solution
, z" r8 x# n5 ~: u268 - Cohen's d
3 \/ y4 d6 Y6 B8 r$ `' y' Z" T" a6 S6 Y269 - Cohen's d Solution $ r) X, A* l$ B
27 - Summary
$ i8 V5 r7 k6 d' H# q$ T5 j3 Q# }270 - r^2 $ `' f% j4 Q+ k1 W
271 - r^2 Solution
: D% M5 f' ?' k# ]& I272 - Margin of Error
' O; G4 a" G: l; E" t; ]( u273 - Margin of Error Solution
; \$ }7 h, ^" I1 S4 z, X7 [2 c274 - Compute CI
Q8 P r, V1 P# p! O( N! y7 D275 - Compute CI Solution 4 U I( u3 T, I. S# w
276 - Independent Samples ! v1 b+ n8 X# [ T. r
277 - Standard Error
: }% Y9 K! s/ l! B) F$ q) g Q8 h278 - Meal Prices
+ g" O$ N) J! p: c, ~279 - Meal Prices Solution
, F, |$ M8 _2 T$ Q/ m% E1 b# U28 - Mean of Treated Population $ p: }2 u4 _8 D4 T7 M% u
280 - Average Meal Price # W. k& n) Y1 x5 e' v
281 - Average Meal Price Solution
: q. b" n- v% H282 - SD for Meal Price 5 u. r9 [0 J$ F! _* p
283 - SD for Meal Price Solution 1 Y# o( b6 ]$ k9 ]& T: C
284 - Meal Price SEM . L" b2 P9 x- u
285 - Meal Price SEM Solution
+ Q- t- v# I- | R5 U6 u286 - Meal Price t-Statistic 8 C+ E5 m2 d: l8 U% a9 S0 O
287 - Meal Price t-Statistic Solution
" M" F$ `$ v6 }# a$ n+ p; ]288 - Calculate t-Statistic
& j) [/ B5 X8 w1 r" t* u289 - Calculate t-Statistic Solution
/ S; x7 e7 n( [) F! ^* x9 K' c29 - Mean of Treated Population Solution & m7 `1 P4 n3 A+ \
290 - t-Critical Values 8 R H, E; v: [1 C( b5 A6 u. E
291 - t-Critical Values Solution
1 k! V2 n# m5 v: m8 p3 Z292 - Gettysburg or Wilma_ & P+ [+ c) H( h- c, A
293 - Gettysburg or Wilma_ Solution
! F4 T) d0 g# y9 }$ X8 [- p/ |2 Q! N294 - Acne Medication
- e' \: N( X8 g; `# C) H; ?295 - Acne Medication t-Statistic
3 U8 f E, M$ R: \3 p296 - Acne Medication t-Statistic Solution ' ?+ K* |; R, r8 F9 D9 x
297 - Acne Medication - t-Critical Values
; N$ b. U5 v) ^; x298 - Acne Medication - t-Critical Values Solution ; Q: a. F7 h L- U) P
299 - Acne Medication - Decision , u: F, n/ P4 o0 x0 k# |* k. `
3 - Klout + T5 x" \. }- A$ T7 V0 Y
30 - Population Mean vs. Sample Mean 5 @7 h3 J# M& a; j
300 - Acne Medication - Decision Solution
$ Y: l* W! h3 ]% ?301 - Who Has More Shoes_ . a6 k+ r* t' T9 L8 N: W9 z0 `5 X0 k
302 - Mean Number of Shoes
- D7 _. _& E% O303 - Mean Number of Shoes Solution # `8 X: {: \& v1 z0 b
304 - Shoes - Standard Error " T2 E* ]+ `% x2 X4 }
305 - Shoes - Standard Error Solution
% k" C9 f: l3 T! a8 r! f1 Q306 - Shoes - t-Statistic
9 E$ q. C' \, m" |307 - Shoes - t-Statistic Solution
6 K, f8 u/ |% q2 G- a9 ~' v; Q- y/ \: a308 - Shoes - Decision
; B3 d- E# M# r309 - Shoes - Decision Solution 4 j) a, G4 r' ?' X! Q4 n
31 - Population Mean vs. Sample Mean Solution 4 x, ]# Y3 Q0 j% ]. U6 l6 M5 z9 i3 r# Y* J
310 - Shoes - 95% CI
1 ?/ S, f" Z, m7 g% B4 G6 r311 - Shoes - 95% CI Solution
6 {; O4 i4 `) L+ f4 ^312 - Shoes - Calculate CI + C7 P) G6 M+ j1 p) o3 F* d9 _9 Q
313 - Shoes - Calculate CI Solution # | s& m2 H) e& g' l
314 - Gender and Shoes + v: |9 f% Q, L/ @/ A$ A
315 - Gender and Shoes Solution
2 n- C3 Q- c9 x4 D316 - Pooled Variance Sum of Squares ) z( ]% ~# o( R) n
317 - Pooled Variance Sum of Squares Solution 5 M) X3 e s! M- I+ H8 W
318 - Calculate Pooled Variance ^5 i7 k; |4 v, Z
319 - Calculate Pooled Variance Solution ) V* z4 R0 B+ p
32 - Percent of Sample Means $ o9 v2 }6 L, x% s& T! ~
320 - Corrected Standard Error
" f% x& S9 }# N5 N2 o$ e2 `321 - Corrected Standard Error Solution
1 X" _! l9 k2 h! O2 v& D322 - t-Statistic 0 l; u& F! {- s0 z. I( e/ a2 ?
323 - t-Statistic Solution
2 a4 M3 G* `8 s. l324 - t-Critical and Decision / L: e: n! |1 y0 `
325 - t-Critical and Decision Solution
" L# S) A( m8 B( t, d326 - Assumptions
) H" {8 p* p& O+ |327 - Intuition
* u V3 h3 |! A1 d328 - Intuition Solution
f) i% y# Q+ q9 X0 c! b329 - Number of t-Tests 4 V2 w, g* @7 t7 V% [2 b
33 - Percent of Sample Means Solution
# S' D0 q& }' n, T# {% }330 - Number of t-Tests Solution + x3 Z" n: E- d% s
331 - Extended t-Test Numerator ! b- @ q; I( T6 x" G _; j) e
332 - Extended t-Test Numerator Solution - a. x, V+ n! x6 J" d) w
333 - Grand Mean . h5 V3 r3 i+ P" a' R
334 - Grand Mean Solution
8 v& \. @# I& ]8 y9 P- Q# i335 - Between-Group Variability
# p) J' ]- [- B9 m2 P# h336 - Between-Group Variability Solution
4 J9 i' M* h( d1 i337 - Significantly Different Means 3 @2 w6 H' a0 m6 Z7 F
338 - Significantly Different Means Solution 5 X, @0 N. B: ?! V6 N1 s
339 - Sample Variability and Significance / E8 W; \' m' h, A$ ]& C
34 - Approximate Margin of Error
( Y; E, @9 C( [340 - Sample Variability and Significance Solution . T0 `+ @, P% k' E1 N- p5 O: w0 ~
341 - ANOVA
& k$ T1 ~0 y. N/ j* n4 P342 - Hypotheses
0 T3 m/ O6 Q5 T! ?2 P% s343 - Hypotheses Solution
% G$ o8 E+ S: D$ M0 I344 - Within-Group Variability ! `! U* x# N+ O' Y6 t" K& \. Z
345 - Within-Group Variability Solution
* R6 d9 H" v6 H8 b! V346 - Between-Group Variability + v* I4 A$ ^! ^# c- _$ i% Q
347 - Between-Group Variability Solution 0 w! L3 E7 ?1 n; K
348 - F-Ratio
' M& k& M! |- _! o6 ]9 v% ^) @349 - F-Ratio Solution ( a6 K4 R6 k2 B6 e ?. O& V* m
35 - Interval Estimate for Population Mean
2 I6 A2 N9 D* B# g$ }) n; N- m350 - Visualize Statistical Outcome ) ]5 e+ o" F+ |' t: i0 J
351 - Visualize Statistical Outcome Solution
4 ^) x) ^0 m; d' x) `( T- P7 g* y352 - Formalize Within-Group Variability . D [' O; t$ {: B1 F1 q
353 - Formalize Within-Group Variability Solution
4 b6 |: x" {: B5 g% e1 O/ I+ ]354 - Formula for F-Ratio ( Y% ?5 B5 H d3 b) o
355 - Degrees of Freedom 4 p) }9 p6 o: }4 G% W; L# Y
356 - Degrees of Freedom Solution
7 X5 H7 y. T( I- y$ Z! [" K2 c357 - Total Variation
4 z2 i J3 J8 E9 W0 Y( R358 - F-Distribution 4 `- Q+ T* N" [* { W' ]
359 - F-Distribution Solution
" b a- J* I& c* I; w5 L( L& W! \1 M36 - Confidence Interval Bounds % x+ a% D) e; `
360 - F-Distribution Shape 2 a( }7 X$ w. u* ]" B3 C6 q W$ r1 }. N
361 - Table for F-Critical
6 n5 h/ M- r; ^+ R/ K$ Z% O3 m( i _362 - Table for F-Critical Solution 1 t* Q- o9 q7 W& l5 Y$ V- O) Q$ B
363 - Sample Means and Grand Mean 6 k+ e) k/ m: Z; k
364 - Sample Means and Grand Mean Solution
+ \5 A I. U& n5 q0 S365 - SS Between
" J) N+ e0 E* `, g+ V1 m366 - SS Between Solution ) i0 p0 F- w* F; d& N2 H0 V
367 - SS Within
7 k) T- x- L# P6 u0 Y f368 - SS Within Solution 5 L+ @$ e, e+ J
369 - Degrees of Freedom
7 Y+ T$ P9 x: o$ w3 U6 p w4 ~, ~37 - Confidence Interval Bounds Solution
% h7 {$ e3 j0 }$ V370 - Degrees of Freedom Solution # F- p$ v4 i( s- R6 X
371 - Mean Squares 7 K; I- E/ ^ T' w
372 - Mean Squares Solution
4 a6 m: J' f( j8 f4 E: f9 f- L! j* S373 - F-Statistic
2 R8 l7 P; \, k: T' u374 - F-Statistic Solution , X1 L; Y; b2 C& ^- ?
375 - F-Critical
9 @$ D4 ^% X7 {5 W0 H8 v376 - F-Critical Solution # t) B0 h- H6 T2 Y+ q; U
377 - Decision , A1 ], s3 i7 W* y- \. _
378 - Decision Solution
- I6 X# ^+ H) [379 - Cows and Food ; m' ^6 r# j$ f3 y
38 - Exact Z-Scores
1 G2 V4 L& z' K$ }380 - Cows and Food Solution
2 v |$ T$ u% x/ ?. j9 Q381 - Grand Mean
5 n8 E# J# T$ \/ B9 @382 - Grand Mean Solution
: c. R% c4 a3 u383 - Group Means
4 A/ T/ e+ V9 D2 u Z384 - Group Means Solution # P" u" ?, S+ Z
385 - SS Between
% \8 O5 b6 \+ u3 E9 Q. r386 - SS Between Solution 9 X& d5 l) h# f! O* h
387 - SS Within
+ C' H: y- R V3 H388 - SS Within Solution
% z P: x% F5 \4 [* V1 J389 - Degrees of Freedom
! o7 A5 C/ A s/ W; z39 - Exact Z-Scores Solution 7 v! K- K6 f9 p6 R3 k
390 - Degrees of Freedom Solution 3 t4 U+ k9 S) {. p
391 - Mean Squares
5 |) Z: q+ w- A1 R v' q3 S4 F392 - Mean Squares Solution
6 P5 p. L# S+ B+ n7 c- E393 - F-Statistic ' p: j T# [5 t8 s* {; ]
394 - F-Statistic Solution
9 Q8 b. u% O# I' }; T Z395 - F-Critical and Decision % |4 C" L1 {: Q; N' P% d
396 - F-Critical and Decision Solution 7 Q5 e3 S% V% m1 ~( @' o7 H
397 - Deviation from Grand Mean 3 B2 P L6 Z& ]# |) ?
398 - Deviation from Grand Mean Solution
V0 L; `4 V) [! y5 e& a! Y399 - SS Total ' ~& Z0 T! \' _( c3 r
4 - Klout Parameters
' u, B; [6 L1 M) y40 - Sampling Distribution ( i! r5 k: H& b7 T: C
400 - SS Total Solution
8 W' x% I* S; l, w8 e" [% m( y401 - Conclusion 3 M; v* ~3 Q" o1 j
402 - Conclusion Solution
3 b) \" u8 u7 o# }# P403 - Multiple Comparison Tests + v5 d7 }! S$ h, x* y
404 - Tukey's HSD 4 \1 c# X0 R( h3 N
405 - Tukey's HSD Solution
/ L* S2 o1 j7 o. _) ~! p! ^) j406 - Which Differences Are Significant_
) T$ o1 s- r# H( E9 A/ E1 m3 Q: }407 - Which Differences Are Significant_ Solution 0 m+ A/ W$ t, j$ }1 I
408 - Cohen's d for Multiple Comparisons
) }) h+ B5 `, ~6 L409 - Cohen's d for Multiple Comparisons Solution
/ S3 S1 z' a, |9 ^41 - 95% CI with Exact Z-Scores ) s+ V9 M( u. s8 y6 Y7 T7 e k, q
410 - η^2 1 A, i4 A/ a) u3 K4 L
411 - η^2 Solution : v y( ^1 L- l* ^
412 - Calculate η^2
1 L+ }: \- H3 S5 T. w413 - Calculate η^2 Solution 5 f/ ~/ v ?7 V) n* G
414 - Range of η^2
; ]* w. Z6 S. D* p1 R0 a( r/ i415 - Range of η^2 Solution
8 b7 m/ ?+ {! r7 C2 `. Z4 |0 z416 - Software Output
3 v P. U% T* |- ~4 O' p# Y/ M; l6 o417 - Software Output Solution
- F" C* l. H7 }418 - Missing Mean Differences
2 e& S3 T/ f0 j419 - Missing Mean Differences Solution
7 I. c/ t! A9 N- E# n" h42 - 95% CI with Exact Z-Scores Solution
6 y: m5 M# C+ j420 - Different Sample Sizes
$ ^4 f5 s% d0 h& g421 - Different Sample Sizes Solution % P* u! ]6 i* o
422 - Grand Mean
0 O7 R( H- ~3 o# z3 U% x( R423 - Grand Mean Solution ]/ V; q4 t: r
424 - SS Between : g! w6 i {2 S7 o) P4 n% W
425 - SS Between Solution 1 {' ^& {8 u) S6 e X6 {& c4 Y
426 - SS Within + t# ?3 Y4 t* V% L' U
427 - SS Within Solution ; g; i! X( A( ?" T$ B
428 - Degrees of Freedom / z# m) }: n* K( |
429 - Degrees of Freedom Solution
/ X% W* \% _5 E3 v/ p' B0 D43 - Generalize Point Estimate 3 t0 S) b) l& ~" f6 u, M% [
430 - MS and F L2 G5 y/ ^, [- n1 b
431 - MS and F Solution
5 ]6 W' j& N' n! k1 c2 [% y432 - Proportion Due to Drug Type ) O' r, I$ C1 c' g: i7 l" L A+ j
433 - Proportion Due to Drug Type Solution
7 H4 {& f; f) @ B# v' T434 - Power 6 m7 e9 f1 U: y9 q% z. _
435 - Power Solution . Z* {& n. b$ ^
436 - ANOVA Assumptions and Wrap-Up
' k' S( z0 g) c7 q P0 k437 - Relationships
' J6 l' K7 F @6 L438 - The Variables x and y
* S2 W7 B" e: z, P439 - The Variables x and y Solution + Y0 G1 J) B5 {! }- ]
44 - Generalize Point Estimate Solution
1 V( f/ }( ]$ _" [ ?440 - Show Relationship 8 e" e1 k' @$ W
441 - Show Relationship Solution ; A7 l8 }6 i, T! a9 G
442 - Scatterplot
. k" ?' B" |. q- Y443 - Scatterplot Solution
. Y" g6 N4 \+ r444 - Stronger Relationship ) l% v% ~4 d; S# x
445 - Stronger Relationship Solution
/ Q9 S$ d4 s# e/ E! ^& n446 - As x Increases ( [- N9 M8 V2 B6 x2 [
447 - As x Increases Solution
- q9 ~; U$ }" l/ P! a7 K4 H448 - Strength and Direction ; m7 X n+ F0 c) E ]7 p
449 - Strength and Direction Solution
2 ^+ [+ v n% N& E8 m45 - Generalize CI
1 V6 f. |! g3 h450 - Correlation Coefficient ' r& X, w b3 L2 Z* w
451 - Match with r ' s" [2 a7 s2 i) g9 g3 a
452 - Match with r Solution ( @5 K" l. `' v# e/ U4 h" Q
453 - Age in Months and Years
" ]) P) @3 b* f/ P1 I& C; T454 - Age in Months and Years Solution
{+ O" y$ d% q8 N0 |" _$ N455 - Hours Asleep vs. Awake
9 @+ b7 D& f% F; n5 ?' E4 D( u456 - Hours Asleep vs. Awake Solution
1 z$ J- Z; I& _: m5 u% B457 - Create Scatterplot
* |/ P8 ?5 ~2 J! T' R% C4 r458 - Create Scatterplot Solution * ~ y7 `$ s# v" v# i
459 - Calculate r 0 F( U( z1 l: j' J
46 - Generalize CI Solution
- S7 P9 h" b& b460 - Calculate r Solution
4 } }7 Q$ Z8 G) R5 ?. L; e+ C461 - Stronger
2 X } f* a9 r) ]+ S462 - Stronger Solution
' p" {9 k3 Z& z463 - Hypothesis Testing for ρ
7 X' g& W7 C) [. t464 - Hypothesis Testing for ρ Solution
9 D( r$ v; E2 P" I0 o465 - Testing for Significance
. f$ D; ?6 U4 M7 L466 - Testing for Significance Solution
" U2 V$ L! _9 d/ m467 - CI for ρ
5 K$ P2 G3 z6 b" w4 i468 - CI for ρ Solution 0 y2 f; L" n& H: Q( |7 F
469 - Find p 1 G/ O& l5 }) R7 h
47 - CI Range for Larger Sample Size
' l2 M( r( @) u( C, d2 @* {' t470 - Find p Solution 8 Q2 X: w& J7 B* Y2 ^( \; G
471 - Add Outlier
) w/ y. A/ p- j# r) @/ `, ?: A' f472 - Add Outlier Solution
) y, U2 X, R* a8 D" l: b473 - Correlation vs. Causation ' ~/ }! c" \4 O: h0 l. ^& f# Y# B
474 - Fallacies & Q" n* U& t& N
475 - Intro to Linear Regression
$ i* `: ^1 A1 w- H4 Y* E6 w! V476 - Airplane Flights
; x/ r/ h% p( _7 e0 G) ~5 u477 - Symbolize Regression Equation ' G" J8 ~$ j; x8 l7 B
478 - Symbolize Regression Equation Solution 1 Y+ O9 \5 x) R- x! h
479 - Guess Best Fit Line
& I8 c1 y2 b" E1 i& n# p7 K48 - CI Range for Larger Sample Size Solution
" U8 c+ R7 y' @% @& D- A4 Y480 - Guess Best Fit Line Solution
7 q5 k/ b3 P/ Z8 T" [481 - Minimize Sum of Squares ' O+ e! W8 w4 b& [
482 - Calculate r
5 Y* {$ N ~4 x9 \" M$ O483 - Calculate r Solution
" z; N4 g% ^8 r( j+ L5 ?6 Z' P484 - Calculate Standard Deviations + V! w& s# E5 ]# ^3 r! |
485 - Calculate Standard Deviations Solution
! Y/ n7 `& q3 b/ e486 - Calculate Slope / ]! _2 a+ g. @( S
487 - Calculate Slope Solution
: K0 |6 K8 Q! ~4 [- k5 G488 - Find y-Intercept
% Z9 J, R. R x9 P489 - Find y-Intercept Solution ( Y% j! c4 \; n% J9 t& e4 B* @0 G& {$ T
49 - CI When n = 250 ' g- D$ V+ ~$ ~, u. _ I
490 - What Point Does the Line Go Through_
9 w. C/ L% u* \, z' Y1 Y491 - What Point Does the Line Go Through_ Solution
/ E( Y5 W0 p* r492 - Calculate Means
% d5 z( j& Z! |3 j8 d3 D+ w. d493 - Calculate Means Solution # ~. S( N( I$ I7 J& c0 y2 i3 x2 F
494 - Calculate y-Intercept
9 i6 ]7 p" S2 H495 - Calculate y-Intercept Solution 1 J8 `# U' x3 g# ^
496 - Travel 4000 Miles
) X) a5 C5 w# K g0 O497 - Travel 4000 Miles Solution
, z2 R8 H5 @6 I% D; e# o, f498 - Additional Cost per Mile
5 N; `$ ~ G2 S; b. p9 g! Y5 T' d499 - Additional Cost per Mile Solution
9 ~4 x9 [2 U+ S) `/ y1 N* [5 - Klout Parameters Solution
; |- \, v" ?$ ^50 - CI When n = 250 Solution 6 W" v/ y2 j6 r5 c8 \6 T/ i
500 - Cost to Travel 0 Miles . W) w: D8 t( k6 F9 Y1 E
501 - Cost to Travel 0 Miles Solution
4 `! e- W, B+ Z, t/ \502 - Travel on a Budget , n `5 {4 M" Y' I
503 - Travel on a Budget Solution
- `0 F2 U9 ~0 ^* P504 - Which Has More Error_ 4 h* K/ H* T' d6 P0 H. `6 H9 m
505 - Which Has More Error_ Solution 0 x$ v: D7 y. M( s: O
506 - Standard Error of Estimate 1 u( k0 v' |; R+ N) j
507 - Confidence Intervals
* S* o# b% ?+ t* _- G2 e508 - Hypothesis Testing for Slope
. ?% K* X5 V+ p" F- L* P509 - Hypothesis Testing for Slope Solution 5 t. \' S; i# w- w. j. ^# j
51 - Bigger Sample, Smaller CI ' s+ z( P( @: G- r2 G
510 - t-Test for Slope
; _" E" E$ i+ e6 m8 S M511 - t-Test for Slope Solution * y! b8 Q0 m5 r( [
512 - R Output
% G" m! ]# y, q513 - Factors Affecting Linear Regression / V: C) D& M. M! d
514 - Summary of Linear Regression
, R5 m/ V3 F! F515 - Intro to Multiple Regression
, \( i* @1 b" y1 u" J+ A516 - Alcohol, Religiosity, & Self-Esteem
1 d0 p1 w# I9 @ T; h2 E8 H517 - Alcohol, Religiosity, & Self-Esteem Solution
3 W$ x: F' `" _6 U518 - Make Predictions
2 a( _2 m+ P: ?8 ?5 T519 - Make Predictions Solution / B0 F# j2 l0 e' Q' A' i
52 - Z for 98% CI
7 l/ k, G; b) b6 E520 - Relationship
{" x% ^$ U: X3 E521 - Relationship Solution
% Z9 q5 ]1 }0 D& W6 H4 V522 - Causation
: p. j7 w" H! h523 - Causation Solution
`. V: e% `* R524 - Applets 2 d* O4 Z) i- K# x0 ~4 b
525 - Scales of Measurement 2 N1 @& U/ }2 I# C3 y) B; [8 ]8 K4 m
526 - Scales of Measurement Solution
2 @$ {! M, o" B8 n527 - Choose Type of Data
3 ?, u% m# q+ p0 f528 - Choose Type of Data Solution
# b* U9 q* B7 w6 X0 K) l5 J6 \529 - Non-Parametric Tests . \$ ~- Z( L0 C9 J7 V4 d; q
53 - Z for 98% CI Solution 6 {" Y2 ? l. b, X3 d
530 - Mount Shasta
- {; I7 Z: m9 s7 e1 B531 - Mount Shasta Solution
% U. y K9 G: _3 a$ v1 o532 - Expected Frequencies
8 ?+ _/ _' }9 S# ^% U533 - Expected Frequencies Solution - |: C, u6 ]5 j" v# ]/ C$ g
534 - Observed Frequency # w0 A3 Q! q# ^7 v% m N, y
535 - Observed Frequency Solution
) p4 L3 b7 {3 T! E( W) ?536 - Hypotheses Percent
' ]0 F0 V+ N7 f1 y537 - Hypotheses Percent Solution + l$ b8 A4 p& d
538 - Hypotheses Frequency j" M0 W( l7 Y
539 - Hypotheses Frequency Solution
+ b( R% X3 C6 C/ M7 j% j54 - Find 98% CI ; ^" Z: m: u$ l% B" Y
540 - Expected Frequencies - p/ N' }; s% C. O& T, W, s9 @8 t
541 - Expected Frequencies Solution 6 H0 ~) c. T! Q Y$ G6 o8 E6 e
542 - χ^2 Goodness-of-Fit Test
7 m" X; ], ]9 O/ c' r1 o/ s543 - χ^2 Statistic ( r9 Y! C) E- e
544 - χ^2 Statistic Solution , ]0 S1 Q1 r- @. j. d( x( g
545 - Observed Equals Expected + O# E# J B# V& a+ j% s
546 - Observed Equals Expected Solution - P3 z# a, P N. q+ {
547 - χ^2 Values
: Q% f5 v1 Z- N0 _( \548 - χ^2 Values Solution
! a* M; N. b5 i* p' k+ o* G549 - Degrees of Freedom # ~; G7 t) w( m( f0 k" {. x- S3 w+ x
55 - Find 98% CI Solution
2 K9 o' L* }. }' u9 R- r550 - Degrees of Freedom Solution
" d* R& B, i3 T: |% q4 f5 {3 @551 - Which Has More df_
+ Z* n4 @& V! q552 - Which Has More df_ Solution O/ L( D3 z$ Q) j6 s5 u
553 - Calculate χ^2 Statistic + t: N% l+ C q _
554 - Calculate χ^2 Statistic Solution $ C ]% z" C! T
555 - Find df & _) e8 S8 y& d- S4 S& c& m
556 - Find df Solution ; w& g% `. F; T2 {" g- ^
557 - Calculate p 0 x% H* F7 A6 a: X$ J' p
558 - Calculate p Solution
2 l) c2 r$ B1 z" V$ r559 - χ^2 Test for Independence
1 ?& X* `+ z$ W1 H4 O56 - Critical Values of Z
2 ^" Y2 Z) x' A {% ~560 - Remember Details 0 [) h$ [1 G9 p4 w& z1 [, Q( b
561 - Remember Details Solution 7 z2 k- D% Z; J( V
562 - Broken Glass
]1 V- m- ~# a+ p0 P& y/ P563 - Broken Glass Solution 4 `* v! L( S9 l7 E
564 - Expected Frequencies
( {. e% G+ f0 v w- q565 - Expected Frequencies Solution
* w" } l) _7 B0 `' L0 p9 i" @566 - Calculate χ^2 Statistic
# Z/ ]5 O/ Q: J! {567 - Calculate χ^2 Statistic Solution
w1 {" M4 @; x& L* S! v1 W, o2 w568 - Degrees of Freedom + X, M& `0 [5 Z$ t5 J) j l
569 - Degrees of Freedom Solution
% v9 D3 `1 z0 F7 M9 V$ e# l57 - Engagement Ratio ( d2 O& {& U1 w! h2 c
570 - Decision 1 v1 q0 D$ W U% A1 u
571 - Decision Solution
2 Y! x) o) Z( n' w/ X7 a572 - Effect Size 4 [ n! l6 e6 g( K# q3 C( ~# A
573 - Effect Size Solution
, O7 q6 E% T3 m1 u574 - Calculate Cramér's V
6 ^: ~. s- N& H& q575 - Calculate Cramér's V Solution 2 ], Y5 [" a3 W6 ]: ~% ?
576 - Assumptions and Restrictions
, Q, J9 ]: P# Y- E577 - Summary
; ]( e% c$ s8 l( G% a6 G578 - Congrats 3 ]0 k% a: o) i6 H( k
579 - Lauren's Outro Video
X$ w# ]% U' S6 i$ m) E7 Z8 o58 - Engagement Ratio Solution
+ e: B# Z" t; D5 n580 - Tutorial
' m, m) f! n! j% q$ X59 - Hypothesis Testing Song + X6 K5 w7 ?% ?8 ?0 R0 n* Z
6 - Klout Sampling Distribution (Mean) ! |/ u5 J' E2 o8 @ t$ h# \
60 - Point Estimate Engagement Ratio
( w! u4 s# L s: K61 - Point Estimate Engagement Ratio Solution ( L$ N8 n% E4 P. [+ M6 a( |
62 - Standard Error , L6 I( ]& U7 K% ^7 { T
63 - Standard Error Solution
5 w8 |. K; ]+ i2 {64 - CI Bounds
. y; L% O# `: g( u4 Z1 Q w65 - CI Bounds Solution
1 i% Q% ^ x" D5 P% M66 - Generalize CI
* s& K, w& p, p3 c( l Q, ? A67 - Generalize CI Solution ; E/ @0 I1 |2 F$ _ _
68 - Margin of Error
7 x! p) Y8 Y5 S69 - Rate Engagement and Learning * i ~7 b6 O5 g
7 - Klout Sampling Distribution (Mean) Solution y/ \+ K: r2 N; L' L6 | [
70 - Rate Engagement and Learning Solution 1 Q. @% f" ^* p. W' z. i
71 - Results from Sample # M, T" M! Q+ F n) E0 i
72 - What Statistics_ ; R+ f7 ]+ N6 h0 f
73 - What Statistics_ Solution + O3 S' z$ i3 s3 M& K, N6 [
74 - Sampling Distributions
# d3 Y' u1 N7 b$ S75 - Sampling Distributions Solution 6 W$ z' o8 f: r; |; u/ ]
76 - Z-Scores of Sample Means
: h) R6 Y6 _, E( |; m9 u77 - Z-Scores of Sample Means Solution - U2 D5 l4 W7 v, O; P! T5 H
78 - Probability Sample Mean Is at Least...
+ P2 c' ?: d( i79 - Probability Sample Mean Is at Least... Solution " B& C8 Q- K5 H7 X
8 - Klout Sampling Distribution (SD) % R0 [+ v6 @) d0 V; b
80 - What Does This Mean_ " |3 j; b* e$ r7 v6 ~( t9 n
81 - What Does This Mean_ Solution
- K5 {/ ~$ H8 d* n! a+ u* N0 e9 N82 - Wrap-Up 9 ^' }3 U2 s1 N% S
83 - Likely or Unlikely 1 {) B# e3 Y6 m
84 - Likely or Unlikely Solution
( ?$ D" e9 E- [- {9 ^85 - Alpha Levels
- q5 P- r% k @86 - Alpha Levels Solution
7 l( H) e$ k3 e87 - Z-Critical Value 0.05
, B% C# _5 A7 r% q) ]3 x88 - Z-Critical Value 0.05 Solution 4 t' f; |( [/ D' [- V5 w
89 - Critical Values 0.01 ' V5 Y# N! K) ?$ H" W
9 - Klout Sampling Distribution (SD) Solution
, E* T: p0 q$ y) ?. b8 a90 - Critical Values 0.01 Solution + F. ?* t# V% J- J1 _! X6 j/ Y0 S
91 - Critical Values 0.001 8 T+ ]$ Y" |6 @# H
92 - Critical Values 0.001 Solution
3 D8 U, b6 l7 R- {3 `93 - Critical Regions 3 q6 t. t$ ]5 p- u8 V/ y, d! c6 g$ W
94 - Significance + x5 B# K. p7 C% z$ l
95 - Significance Solution
4 |! M/ U6 N3 s% u' e96 - Darts
" |4 \% G( Q' R% `97 - Z-Score : U3 _; |: Z% W& y
98 - Z-Score Solution
" S6 A7 j0 R+ H99 - Two-Tailed Critical Values 0.05
0 i- S, L4 K: t9 jIntro to Inferential Statistics Videos英文字幕（rst格式暴风影音可加载）.zip
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发表于 2022-6-23 19:54:02
