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课程目录' K3 f' S+ g6 F! w% J
1 - Lauren's Intro Video 5 P0 a3 `+ \8 ?1 l/ l: ?5 B
10 - Sampling Distribution Shape ! g1 n) R5 j0 N" ]1 G0 k
100 - Two-Tailed Critical Values 0.05 Solution $ o" u; U: [2 r" R$ b1 V; ?
101 - Two-Tailed Test
7 S# T9 G: w8 j) v* l4 t102 - Two-Tailed Test Solution
% `% s+ t' _3 y103 - Two-Tailed Probability 1 V) g9 _- W. [
104 - Two-Tailed Probability Solution 7 ~" \( D3 z) Z/ b( i
105 - Two-Tailed Critical Values 0.01 ) V+ z0 ?" F" W! s
106 - Two-Tailed Critical Values 0.01 Solution G* z2 @( J+ F1 a8 A6 R1 k& z
107 - Two-Tailed Critical Values 0.001
; ^7 d) c, _$ n ]$ T1 U0 m108 - Two-Tailed Critical Values 0.001 Solution ; L) c0 {4 Z6 ^
109 - Hypotheses
& }7 Q4 }* U O7 |6 K11 - Sampling Distribution Shape Solution 0 {. O/ d z) h) R
110 - Fail to Reject the Null
5 m& Q+ Q- v4 r: O& V$ W; \111 - Fail to Reject the Null Solution
& W0 Q( L: m: k$ {" G0 D* g/ I112 - Evidence to Reject the Null " o; ^+ R! m8 s: [1 H: V+ ^
113 - Evidence to Reject the Null Solution
5 J2 O$ E8 j7 f. y$ L( M: Z3 w114 - Mean and SD
+ h `8 I; b+ L, J! y# P115 - Mean and SD Solution
( J7 y, z" h. |( ?116 - Null Hypothesis
+ s9 c: n/ |- n, k" v7 y: f+ D117 - Null Hypothesis Solution
+ n: e! C+ b1 r3 @# \2 s118 - Alternative Hypothesis ' ^! g* ^% }3 j7 w, }3 }( I
119 - Alternative Hypothesis Solution ! H+ C- t5 q. L$ e" N9 {, n
12 - What Do You Get with a Good Klout Score_
8 R- u& O1 q( w% t120 - One tailed or two tailed 2 V0 ^) h+ t( p
121 - Conduct Hypothesis Test 2 `. ^) E9 O2 [1 E0 M7 V, W
122 - Conduct Hypothesis Test Solution
! v! [5 P, g- x# K, ^. D123 - Critical Values 0.05 , H8 f7 U. m. w" @
124 - Critical Values 0.05 Solution
! D' @8 B0 }5 q* M125 - Z-Score of Sample Mean
5 j* W& p6 S. N2 r3 J9 E3 @% q9 f126 - Z-Score of Sample Mean Solution
5 U4 h9 ^+ E" _! H0 i. R6 I( B127 - Results of Hypothesis Test
* B% t/ v5 j3 p6 k$ u4 p128 - Results of Hypothesis Test Solution # [* J) P0 O- X% m/ t* T
129 - Increase Sample Size ; T1 A- `! |2 o* e r* y+ f
13 - Location of Mean on Distribution
' K; `2 n8 j9 W130 - Increase Sample Size Solution + E: y$ k/ j8 ?& B6 X2 Q( o
131 - Reject or Fail to Reject
( T! ^# u. r7 S3 L9 o- C( u2 c132 - Reject or Fail to Reject Solution % v/ n4 L5 ^- X
133 - Probability of Obtaining Mean 9 t9 ~/ B4 k! A; V, a$ w
134 - Probability of Obtaining Mean Solution 3 s: ~& h( P" T; b/ F4 }6 y
135 - Decision Errors 6 G* y( }2 y! R& x' F/ C
136 - Decision Errors Solution $ n( ^& \# f6 U: Y1 g8 y+ c
137 - Hot Beverage 3 h" B$ K* d, k1 W1 Y s
138 - Hot Beverage Solution
6 H* Y' v( D a; a* B. X) y139 - Raining 6 y- [- O- k* g$ P/ g, P
14 - Location of Mean on Distribution Solution 0 q6 {9 l) F2 e/ r# r: s- D: X8 E3 u
140 - Raining Solution 3 O( E% h: c5 k
141 - What Happened_
: W T& q; U v142 - What Happened_ Solution , d' i6 l& _5 E* ?" i. t
143 - What Happened_
/ T4 B! `4 t) Z8 ~9 R144 - What Happened_ Solution % V$ w" v( q& o
145 - Prone to Misinterpretations 8 x9 U+ [/ _6 Y! O) p- @
146 - To Finish This Lesson...
5 ^7 F9 |* P' }147 - Hypothesis Testing 0 q0 U. s, S7 e9 F
148 - Increase Engagement_ # i! u- ^# r# }1 D
149 - t-Distribution
+ F8 X% i- N. `9 C* N15 - Probability of Obtaining Mean ! T I2 q% T3 I. H4 E+ B
150 - t-Distribution Solution 7 b' r3 m$ b/ X$ F) t
151 - Guinness
; o- k0 P# p% p4 @4 n% w1 B152 - Degrees of Freedom
- M* _7 i. A a' i, o; E. }153 - Degrees of Freedom Solution 1 [( z) k5 Q& u9 I
154 - DF - Choose n Numbers $ v# o# f. @7 O9 w: m' B4 {& g
155 - DF - Choose n Numbers Solution 1 H. k# p* p" l2 s# j% t2 X
156 - DF - Add to 10
: S0 h) M& W3 n157 - DF - Add to 10 Solution
1 {5 A# P! N6 `, T7 U" W158 - DF - Marginal Totals 6 s# k, z8 n, h9 J* Q
159 - DF - Marginal Totals Solution
" Y; ~. C' \: d/ V% O6 _; s* k' A4 \16 - Probability of Obtaining Mean Solution
# l% C8 N$ Z; F; A, h160 - DF - Sample SD 0 Y6 v- u) s, @% j" U9 E
161 - t-Table 8 S' V+ w8 n4 N/ ]) ?
162 - One-Tailed t-Test 9 v. {7 ?) n8 F* W
163 - One-Tailed t-Test Solution
' S2 d& d. h( D9 _9 M6 z" B. d( d164 - Two-Tailed t-Test 3 l# {# I+ K1 ` L& o f3 `
165 - Two-Tailed t-Test Solution - O5 a1 ~5 E+ b: T( G i7 f8 y8 b
166 - Bounds of Area 2 `4 ~) x" F/ E; Z
167 - Bounds of Area Solution m% P9 \+ v" L; A5 T* |8 O2 q$ G k
168 - Affect t-Statistic 4 |2 J" [3 \9 u9 b8 v2 {6 z5 y
169 - Affect t-Statistic Solution 9 t6 w. ^2 [) p
17 - Does Low Probability = Causation_
0 A4 D) k [( b- ^; M' t6 u170 - One-Sample t-Test
+ o* R6 i- ^8 V/ |" [/ _171 - Increase t
; A, X; E m2 Y172 - Increase t Solution 4 Y. I, a) T1 g, F
173 - Finches ! _1 O+ x4 {8 x) @) } {) L) J
174 - Finches Solution - Q' ~/ S# B9 W- |5 C5 M
175 - Finches - n and DF
1 M! A" |7 O2 l& Y) @176 - Finches - n and DF Solution 8 |; z' O% ]7 K# E
177 - Finches - Mean and s : C% `; t, L0 w+ C1 b) G
178 - Finches - Mean and s Solution
& M9 H7 \: z9 v8 o7 o179 - Finches - Find t-Statistic 4 m/ x3 E U6 V5 @- y
18 - Does Low Probability = Causation_ Solution " S- Y9 Y6 N/ W, F( n4 U+ Q
180 - Finches - Find t-Statistic Solution - t1 c% A: T# M0 U' P: o
181 - Finches - Decision
3 k. i# L$ X0 Y; D182 - Finches - Decision Solution
4 U1 x: |; m- o/ z: X183 - P-Value I% i4 ]0 [, Y7 u& ^, i
184 - P-Value Solution 2 s1 n, X- a' f' Y" j6 g( t2 W& A
185 - Visualize P-Value
1 Q, N; y2 P# A' z. P186 - Visualize P-Value Solution
% k6 ~: d. z* |" e) ?, P187 - Find P-Value ! e0 x3 F. I7 B$ X" H6 E# [$ [
188 - Find P-Value Solution 5 Z! C) b% M/ P/ c2 ^% w9 V/ B9 l
189 - Rent - t-Critical Values 0 Y* o) e* i. _* L1 V* y9 j- U. J
19 - Increase Sample Size
6 k! ~2 Z' G: T0 Q) a190 - Rent - t-Critical Values Solution
, t) @8 A: m) N1 ]191 - Rent - t-Statistic I- g6 N' q3 V$ k
192 - Rent - t-Statistic Solution 6 _/ u# y G, b" I+ u
193 - Rent - Decision & M) q5 ?3 l U H, U& t' s7 n
194 - Rent - Decision Solution ' Q _9 F: k: I7 B3 J6 K; |4 {& N) v
195 - Rent - Cohen's d . H7 B! k! ?8 |1 f, I
196 - Rent - Cohen's d Solution
6 \# W' I' w" C197 - Rent - CI 9 Z' P1 O5 c3 b( n3 g+ o) i
198 - Rent - CI Solution % i: R3 J, X: X% R# L" H
199 - Rent - Find CI w" Y9 I: \# t! o7 X& N1 f
2 - Intro
$ p. t& ~) t& }& L20 - Increase Sample Size Solution 3 x {! U/ {5 X+ `9 X3 E# Q' B
200 - Rent - Find CI Solution * `. l) i6 t9 N; S% B
201 - Rent - Margin of Error
2 K: M( T2 A- S w1 b* R202 - Rent - Margin of Error Solution . B5 x: ` S g$ Y
203 - Rent - Increase n : K" X& D0 M8 \$ D% K
204 - Rent - Increase n Solution 2 j/ R) C+ e, O
205 - Dependent Samples
6 M# {6 K% l' q206 - Keyboards 9 Y2 O! @! K3 ]" ~) z- W7 H5 F
207 - Keyboards Solution
, E6 m" X- [7 W; E2 S3 O# k208 - Keyboards_ Point Estimate for Difference
- m5 K5 L" J! Z4 p5 H6 A209 - Keyboards_ Point Estimate for Difference Solution 4 j6 f; H! B$ j/ X0 J
21 - Location of Mean
) I0 z6 i; J" _- d210 - Keyboards - SD of Differences ( e2 h" U4 a" ?/ D" [3 P4 e
211 - Keyboards - SD of Differences Solution
p$ O7 [% n: A( M3 H: W212 - Keyboards - t-Statistic 7 O& e$ W* l/ d) W0 a8 d
213 - Keyboards - t-Statistic Solution : r% B. l/ `( g; O3 K9 B
214 - Keyboards - t-Critical Values
V$ u* s2 ]! d* V% B1 O" ]; [' ?215 - Keyboards - t-Critical Values Solution }& m$ A5 V( G
216 - Keyboards - Decision - i) g* ? u$ g. ~: {4 x
217 - Keyboards - Decision Solution 5 l& G! S* M1 D+ S: L1 ]( l2 D
218 - Keyboards - Cohen's d 8 O$ G2 ]& ?$ I T% W; Q
219 - Keyboards - Cohen's d Solution
; |- l, E! D4 P4 |22 - Location of Mean Solution
3 D5 I# k7 E) d8 P220 - Keyboards - CI for Dependent Samples
$ l$ k) q: m2 |% _6 `* S: m221 - Keyboards - CI for Dependent Samples Solution / t' ?9 o) i1 @2 `# B$ i% T
222 - Notation for Difference 4 D' m: U6 c/ S& S+ @
223 - Types of Designs
; R4 `) y( L1 o) i0 o1 r7 q+ E+ P/ h224 - Effect Size
+ [: U- A: _4 e, P- \3 J225 - Everyday Meaning ( Y, X6 P$ ]0 T- O2 L( Z
226 - Everyday Meaning Solution / G2 T# w2 D$ W/ C
227 - Types of Effect-Size Measures 4 C4 Y9 Y$ Y9 M5 V, M; w" |8 O
228 - Statistical Significance ) b& L( U: J) u% v
229 - Cohen's d
7 |7 v0 r7 y9 l$ e) W23 - Probability of Mean
4 L, V3 I9 g6 l7 [# d$ B3 h6 I230 - r^2 1 s9 k! J- X# [$ ^1 M3 @2 v* B- o
231 - Compute r^2
% _- H! b/ o: B2 ^2 l# b: i+ B8 Q& v232 - Compute r^2 Solution
0 U% v% Z6 w4 r233 - Report Results 4 a8 b8 o+ R4 s. @0 I3 l
234 - Report CI Results 5 o* x% a3 @2 o `. A9 l3 K- r/ x
235 - Report CI Results 2
0 R" Y0 P' i9 {236 - Report Results Effect Size
( f4 U8 n7 x3 |237 - One-Sample t-Test 0 |: K& e) h" X! H
238 - Mu * D/ x; S! n* w$ F
239 - Dependent Variable
' \4 e* |) V( j24 - Probability of Mean Solution
8 D; g1 K) |3 S0 E: R240 - Dependent Variable Solution
: ]$ q, z: O6 V+ z( ^241 - Treatment 8 |8 @; {, D6 {; K$ F
242 - Treatment Solution
% H0 S2 i( t9 |5 F# R# W; f1 X243 - Null Hypothesis 0 C' ?5 N0 e: d9 A v% O* y
244 - Null Hypothesis Solution
5 ~8 i& q$ p# J E+ L+ h. K" r$ s245 - Alternative Hypothesis
( g# I, H2 {/ d0 d7 d! x- @; H246 - Alternative Hypothesis Solution . ?1 C, x ?: N" o- O8 Q
247 - Hypotheses ( F9 c' ?8 c* _" O0 X0 a
248 - Which-Tailed Test_ : d: @; [0 ] u# c3 {4 `4 H
249 - Which-Tailed Test_ Solution " d) r; I: R/ T4 D4 D* ~5 F% f
25 - Something Fun
. H# E3 K# W: l( v250 - Degrees of Freedom " @+ W3 C/ H' w! X8 i9 ?
251 - Degrees of Freedom Solution
% i2 B$ e& s$ _. d3 P8 q- v, P: u252 - t-Critical
/ f. J! ^1 z; m' L) G7 A2 q# q253 - t-Critical Solution % [' B# H/ J5 v
254 - SEM
9 ~- J6 a' W9 O, v6 t! Q# H/ W255 - SEM Solution $ B0 q) _% M$ u$ f0 ^" ^
256 - Mean Difference ' |- t0 q8 `4 w1 r
257 - Mean Difference Solution : B9 L2 v+ H( ?1 P
258 - t-Statistic
# h; R5 {9 [6 C# z$ ~7 A259 - t-Statistic Solution
+ k$ `4 [0 y0 }; Y/ u26 - Something Fun Solution
7 M* h* m6 I7 N6 ?3 Y6 N) q& C260 - Critical Region
8 ]9 w3 X- U9 o# H1 \2 g! r261 - Critical Region Solution 4 D* W3 f# j5 k$ K' {7 v: Q6 B9 s
262 - P-Value
% t8 W- w0 S& p+ \; Y* V2 x' a263 - P-Value Solution
/ O. F6 @% A5 V+ Z7 D' A0 h, F264 - Statistically Significant 3 G/ G# \, C: u. b6 q5 L* g
265 - Statistically Significant Solution ; A& t1 \+ B4 s3 K
266 - Meaningful Results $ n9 H% x3 ] f+ y/ f6 ~+ f
267 - Meaningful Results Solution ' W" H/ V/ o. i6 Q. J% }
268 - Cohen's d
6 ~0 u2 |* y8 O$ ?& c7 c3 A& K269 - Cohen's d Solution
6 i: ?- y* \8 U, R* o27 - Summary k! n; M! U2 u) v* ?7 `0 n/ \% ?
270 - r^2 1 c( `% R( |5 @0 Y* X# Y7 s$ V
271 - r^2 Solution 8 g2 E( c& w9 T* g
272 - Margin of Error
6 c' v* |: U) Z273 - Margin of Error Solution ' ]; W& M1 P# w1 y, B
274 - Compute CI
/ \. |4 c! I4 y9 V275 - Compute CI Solution , h u' t+ f/ q# s r o# [3 s
276 - Independent Samples 5 [ T0 s9 w% \) q- Z
277 - Standard Error
% O* Z+ Q# o- m4 @0 @278 - Meal Prices
% i, G7 Q: C8 V279 - Meal Prices Solution 1 V) ^3 B9 V- Q" P) Q
28 - Mean of Treated Population
6 l3 _5 e, M5 H) W280 - Average Meal Price 9 l) ^* _- b. {0 T# \0 s
281 - Average Meal Price Solution
6 s5 f. [' d& w282 - SD for Meal Price 5 M3 E8 X4 A8 u$ m- j7 E
283 - SD for Meal Price Solution
8 ~( e) n$ \; K! d- q3 ~284 - Meal Price SEM , o: ?- r3 ^% m1 y% p
285 - Meal Price SEM Solution
* Y1 k) S+ G5 b# l k p) c286 - Meal Price t-Statistic
$ h9 |9 C- M& z$ ?+ d# {; D287 - Meal Price t-Statistic Solution % D( z. D; c/ c$ ?7 g
288 - Calculate t-Statistic , n! I; U( k+ Y: K( R8 n1 D
289 - Calculate t-Statistic Solution
; h7 u3 c) m2 |9 s5 J29 - Mean of Treated Population Solution ' f9 V6 g- C, P3 o: c. ^
290 - t-Critical Values " w5 k( F! c- G$ Y
291 - t-Critical Values Solution 1 A+ V5 l7 I2 L: I5 h
292 - Gettysburg or Wilma_
" X0 k& v; q5 K! z293 - Gettysburg or Wilma_ Solution 4 k% Y6 k% w% t. R s: W7 v
294 - Acne Medication . G) v8 a! U$ w5 e1 O! d& |
295 - Acne Medication t-Statistic - G! h- f# S4 @+ e
296 - Acne Medication t-Statistic Solution - \/ j- L! U' u8 J- y5 G6 d' \2 ^# N
297 - Acne Medication - t-Critical Values
+ a' u0 m" O* j0 H, [: p1 V) ~298 - Acne Medication - t-Critical Values Solution 1 X0 t! j$ i' u; C
299 - Acne Medication - Decision . O$ f( z$ u# ~7 @, p
3 - Klout # |( j' c, ^4 r. B& s+ B. ^+ `
30 - Population Mean vs. Sample Mean
9 k4 I e3 E/ k( M300 - Acne Medication - Decision Solution
# F I- @- T' a& Z! ^301 - Who Has More Shoes_
7 ]4 t9 {* r! p" I- v302 - Mean Number of Shoes
& y! W3 A4 B; U# R+ |9 Y7 v4 ^303 - Mean Number of Shoes Solution # ]) ?- v) r4 w5 F6 d m
304 - Shoes - Standard Error
, v! X& K; _& w, H% y7 {305 - Shoes - Standard Error Solution
. F; @, }% l' B+ a- b4 l; I306 - Shoes - t-Statistic
9 b4 ~0 D% ~! u$ a307 - Shoes - t-Statistic Solution 8 y; A8 f/ q z, P5 G3 t p. M
308 - Shoes - Decision 6 z+ x, b9 i' u
309 - Shoes - Decision Solution
% |7 V! F& m+ i5 j/ Z* A* L \31 - Population Mean vs. Sample Mean Solution
7 I" W5 ~+ }& R _) \) y" c6 K310 - Shoes - 95% CI 8 R! I1 }/ E8 F3 |, W% S
311 - Shoes - 95% CI Solution
( Q- T7 z) M' z- ^. \3 o312 - Shoes - Calculate CI 0 e$ G6 q# Y4 z' _( T
313 - Shoes - Calculate CI Solution - c+ b/ |/ d. r J5 P
314 - Gender and Shoes
5 ~4 N# E, E4 c: M# a% b315 - Gender and Shoes Solution 1 _( Z* h7 f/ T$ y, }% i
316 - Pooled Variance Sum of Squares 9 u& \* H( L1 d( `' O
317 - Pooled Variance Sum of Squares Solution ' {+ Z7 \- s, s( C
318 - Calculate Pooled Variance 0 E! u3 r8 d. }9 F. @' Y
319 - Calculate Pooled Variance Solution $ ^1 Q- F: H J' w1 I {
32 - Percent of Sample Means 1 w; {* a! ]2 x8 D. U# a
320 - Corrected Standard Error
8 S$ H8 c7 X- {321 - Corrected Standard Error Solution
9 d6 O) M* C8 b322 - t-Statistic
; Z1 J9 W7 g; E1 h7 u( O9 _323 - t-Statistic Solution
' p0 X; ?% J# M# w( y; b" c$ }6 [/ |324 - t-Critical and Decision
0 Q5 z( R6 B, D1 A8 }0 c- D+ j325 - t-Critical and Decision Solution ; K, u0 W: G" K& y- @1 X9 V5 n r
326 - Assumptions 7 _5 s7 F: @' u' \* w
327 - Intuition ; `' X3 v R+ Y9 Z8 n
328 - Intuition Solution
( N* G1 ]( c2 ?8 G* b) z7 `* p& B329 - Number of t-Tests * w. U `8 ]9 [, O! d
33 - Percent of Sample Means Solution
/ q! |5 X s G. [! a6 S, q) L+ o330 - Number of t-Tests Solution
4 p! H9 X: R& s. s( e% O331 - Extended t-Test Numerator
1 a1 m* Z9 y. i( l( I0 M332 - Extended t-Test Numerator Solution
% Q! t A- f; s+ j2 Z9 j9 B. @333 - Grand Mean 5 d3 \% q8 E) b6 f
334 - Grand Mean Solution - @& W4 k7 H8 ]+ J2 l
335 - Between-Group Variability 0 `0 D- \" q; n$ u; t$ t$ l( @& }
336 - Between-Group Variability Solution
{" d9 j: G8 S( O7 B1 E337 - Significantly Different Means 0 n' t# R1 I8 _! Q( q
338 - Significantly Different Means Solution
1 p C# E$ E+ p: H339 - Sample Variability and Significance 1 d1 i0 R, p8 B( D
34 - Approximate Margin of Error
! f: Y+ t* C ? r8 z; d340 - Sample Variability and Significance Solution
4 I& `0 [& o8 i. q; | l341 - ANOVA
6 L9 [* h8 G. E9 e342 - Hypotheses 0 z: B4 C S! U/ v2 M! T1 _
343 - Hypotheses Solution : W( R4 l' v- z; w9 ]8 w4 O
344 - Within-Group Variability - h! m8 x" j- N0 j, p- `% `+ _
345 - Within-Group Variability Solution
: Z+ T& f6 O) e6 X4 `" Q6 S346 - Between-Group Variability
5 U& J6 ^7 z9 _347 - Between-Group Variability Solution
/ j3 Z0 T( K! e348 - F-Ratio
5 X) W- w' |8 P7 U4 g' l349 - F-Ratio Solution ' K' P4 j% l0 H
35 - Interval Estimate for Population Mean ' `: k7 O* O2 g( h) {
350 - Visualize Statistical Outcome
9 ^$ \* K9 D4 _351 - Visualize Statistical Outcome Solution
2 c( `+ Z: ]" ?9 G: f352 - Formalize Within-Group Variability S. w: }3 w# w( ^
353 - Formalize Within-Group Variability Solution
3 j+ f5 x' ?" `/ g2 W! B. m354 - Formula for F-Ratio
# k( [2 _8 \$ N& K( j, R355 - Degrees of Freedom : P' T f* W& A$ S* d
356 - Degrees of Freedom Solution
4 l8 S5 [0 ?6 V$ P! J, R357 - Total Variation
2 C2 C, d( `( m" b$ R+ e$ ~0 Y358 - F-Distribution 8 L$ H% k: j2 T; L( B5 X
359 - F-Distribution Solution , K/ \1 b0 V: x8 \
36 - Confidence Interval Bounds ! c" N# M( D% f# k( v
360 - F-Distribution Shape
1 P: g# w9 {: G5 {! w* o1 k6 i361 - Table for F-Critical
( I8 a* m' n% v. ^7 ~) I$ z; Y362 - Table for F-Critical Solution 1 ~" ?+ w+ @2 r% t2 J& e
363 - Sample Means and Grand Mean
1 Y0 \( A" v- x+ p5 w. `- b' d" o364 - Sample Means and Grand Mean Solution
e" W% w1 S; T3 t365 - SS Between $ R7 _8 c1 {- X3 z
366 - SS Between Solution
2 n8 |- D0 T. Z4 R. S! d9 r367 - SS Within : d2 W, A) |, `$ u
368 - SS Within Solution 9 X: n7 `1 }9 M4 A7 q; w
369 - Degrees of Freedom
( I; ~/ E* p% n% N$ M37 - Confidence Interval Bounds Solution $ O+ v& \& {0 z! X4 i
370 - Degrees of Freedom Solution
& V3 r/ z7 H' E3 O. u* [371 - Mean Squares 7 J& j: L: H. P, g1 W# U! Q* M" C
372 - Mean Squares Solution $ j2 Q$ ?0 e/ y B2 O
373 - F-Statistic / Z; j; w) i) h- y$ h5 v7 d
374 - F-Statistic Solution
) b/ b& ^9 |. u/ z1 ?375 - F-Critical 5 D y% k y$ e) t5 s f% p& C! i* v" n
376 - F-Critical Solution - W; r9 l) L) b* G; A6 p
377 - Decision * L. g! j1 ^- i" x4 j) i
378 - Decision Solution 0 d5 e. S3 s5 F4 O# n. g
379 - Cows and Food 2 q/ B8 u+ U/ `
38 - Exact Z-Scores - D0 }4 B4 r6 c. `2 g' |+ _
380 - Cows and Food Solution
5 ^8 s4 o0 H1 b; p7 w381 - Grand Mean 1 U. v0 w3 E% ?4 W
382 - Grand Mean Solution 8 W& B1 |* a: l) ?
383 - Group Means # [, [/ h g1 [' K: p
384 - Group Means Solution
2 C" |) d$ W/ h k3 y385 - SS Between $ o2 ~$ ?7 S7 R. L) P
386 - SS Between Solution " y" t/ z& Y1 n' N7 p0 U
387 - SS Within
: ?) Y8 C+ o9 ^. z" @& i388 - SS Within Solution
) {' a" l9 Y- ?! t, N389 - Degrees of Freedom
8 k4 f" Y) a4 a8 s2 P' G0 L# t) l39 - Exact Z-Scores Solution
8 d& d1 w9 l2 C/ ^( J; ?$ l7 \( o& j390 - Degrees of Freedom Solution
$ A5 R9 B2 W! d: U7 G$ s391 - Mean Squares
7 e- y( I/ ~/ x392 - Mean Squares Solution ) I+ z, u3 I8 Q" u7 E' z3 _: F; ^
393 - F-Statistic $ j: Q8 \8 ]9 g! b7 `
394 - F-Statistic Solution
/ {5 D+ K& R# h0 r3 r( E& z395 - F-Critical and Decision ! N1 f* l: D. f/ ^: O% l8 Q
396 - F-Critical and Decision Solution
% O6 C' K0 m! W7 V$ m/ R5 [397 - Deviation from Grand Mean # |& N$ w' o* o0 r# t
398 - Deviation from Grand Mean Solution 8 i; m: g- @: u |
399 - SS Total 6 C( |, }4 T0 H$ b
4 - Klout Parameters & P( A$ B" {& U, ~( }* E2 T! G5 ]
40 - Sampling Distribution 8 L9 p6 [- q1 C7 S" ?7 w
400 - SS Total Solution
& n9 P8 V: C9 a, l \' S401 - Conclusion
. B2 U- Y- E+ J; f1 Y402 - Conclusion Solution
# ^2 p# w3 m+ s, l/ ^0 G1 G403 - Multiple Comparison Tests
' d+ D7 @, Z$ t2 a1 ?1 C404 - Tukey's HSD
$ f+ T% q7 ~0 {5 l! Q405 - Tukey's HSD Solution
) C- i" S" b# y' \/ J# X406 - Which Differences Are Significant_
9 ]5 T4 c; L' K4 b) z, a407 - Which Differences Are Significant_ Solution
, p) i9 q9 n) r, }: }408 - Cohen's d for Multiple Comparisons
Y7 s n4 n T: e409 - Cohen's d for Multiple Comparisons Solution
6 h- D, N- b- p" i" d# N41 - 95% CI with Exact Z-Scores ( k" m" R0 u* ~4 D- }+ P
410 - η^2 9 N3 ~2 ]1 H: S$ i1 _) n
411 - η^2 Solution
3 C) e' i$ [; z412 - Calculate η^2 & g- |5 T) t& W( r0 k# B! B7 I3 _
413 - Calculate η^2 Solution + G6 `; |4 _1 m6 r
414 - Range of η^2
0 i; }. ~, n1 p" E6 I415 - Range of η^2 Solution
& t3 x1 T& R" X( D416 - Software Output 4 ] W/ J' k2 E% @( D- G
417 - Software Output Solution
8 E# i' I- i: b418 - Missing Mean Differences % H' W" i& F$ a N
419 - Missing Mean Differences Solution S: d% y6 y4 ~6 Q2 [9 U+ H8 Z
42 - 95% CI with Exact Z-Scores Solution
. R8 N( z- m8 t; N4 G8 z/ s- f420 - Different Sample Sizes ! @9 c$ W2 o9 ~ B3 O! V
421 - Different Sample Sizes Solution / ]; a1 @! O. }! w3 V
422 - Grand Mean b( |7 C7 G. a+ _5 _& q$ O/ U4 x
423 - Grand Mean Solution ' C" I' [, w: x5 v" r0 R
424 - SS Between
& y3 ~& y* w. z425 - SS Between Solution
4 N+ [# u2 X9 q; D* ~+ i) F426 - SS Within
, i i) F4 l. T! O9 `: k# l427 - SS Within Solution # y+ W) l6 i" P7 d1 j% F2 Y
428 - Degrees of Freedom l! F; O6 l# T' u
429 - Degrees of Freedom Solution
6 {" G6 M% A5 k2 f43 - Generalize Point Estimate
- I9 t2 ` Y4 h. I4 O/ Y/ A430 - MS and F " o! i6 P4 o; a4 `2 w' n3 J8 n8 I
431 - MS and F Solution 6 Q# y/ o/ `* [/ ^6 [+ b
432 - Proportion Due to Drug Type
m6 v' _ Q& O$ L; ?433 - Proportion Due to Drug Type Solution ) e6 _+ r4 m/ ^9 x* r" d( v
434 - Power
1 V( M. d* Q, `: y% Y2 N8 e435 - Power Solution 3 L1 Z* q+ t9 J5 _' k( e8 q7 h
436 - ANOVA Assumptions and Wrap-Up
( v5 v" @6 ^% N! K' @' X! d437 - Relationships
6 h6 Y2 c( p* ^: X% V# H438 - The Variables x and y
* O0 S+ t9 \7 n4 y439 - The Variables x and y Solution
1 m5 W; a7 p6 y44 - Generalize Point Estimate Solution
7 ]1 X6 [/ _0 ~# x440 - Show Relationship - h' f: {* S' ~: e" z5 L& j" p
441 - Show Relationship Solution
1 u3 f5 \5 N. s. R0 N0 m% u442 - Scatterplot
# B2 H1 ?0 g3 Y6 `0 B! J4 k9 U443 - Scatterplot Solution & r0 s/ V+ t( K( W7 R2 _% b
444 - Stronger Relationship 2 I+ x3 I [ ?' a: k
445 - Stronger Relationship Solution
- }! _: s/ f! G; z446 - As x Increases
, U5 B) \* Q$ A) F1 U447 - As x Increases Solution
3 \) I* a4 p' \* T448 - Strength and Direction , ^! E- A+ V( B/ Y4 M6 H
449 - Strength and Direction Solution # v* g% g1 {8 X! I
45 - Generalize CI
# D5 E9 w- _/ G+ A: g( N* {450 - Correlation Coefficient 7 X: J3 l5 U- ^
451 - Match with r
' D9 ]: m' H" t7 V% f. O452 - Match with r Solution $ _7 j5 r2 M& F
453 - Age in Months and Years 4 ~; s0 c4 w) o" p
454 - Age in Months and Years Solution : ^4 d; t% I* i. R6 _$ q
455 - Hours Asleep vs. Awake
$ \0 _# L0 p7 y7 r456 - Hours Asleep vs. Awake Solution
+ ^, c- G; f1 K& P% X457 - Create Scatterplot / Z* W; x1 o N% B: W
458 - Create Scatterplot Solution
4 w! e7 {0 [, e6 K459 - Calculate r A7 w6 p7 x/ L6 O, ]9 _- U+ R. }
46 - Generalize CI Solution 1 | W0 V, F4 ?- |* z3 M8 U9 L
460 - Calculate r Solution
! Y$ J/ u6 \2 N- ^8 P461 - Stronger 5 N, f' R3 d& F1 H" u* x5 q% z
462 - Stronger Solution ! v$ U/ @- W2 ~/ f% A! b) n
463 - Hypothesis Testing for ρ
# G: C- z/ P% y464 - Hypothesis Testing for ρ Solution
# \4 c3 @& M( M3 y- v' y+ c4 K465 - Testing for Significance
3 I' ~! p& M: G: [# \# t0 W466 - Testing for Significance Solution , t1 |) a" m+ c: i
467 - CI for ρ
3 d5 K) @, t2 i( A. j" P. { p468 - CI for ρ Solution + U& R# U L; L5 c
469 - Find p ) T& m! \1 ^; l2 b7 E
47 - CI Range for Larger Sample Size ( |* j, ~$ F: ^+ V3 c B( \5 s
470 - Find p Solution $ E3 }! _4 \, c/ p
471 - Add Outlier * i/ ]0 C- [( n* X1 K9 f/ k
472 - Add Outlier Solution ; y; c, h& |2 t4 v7 [
473 - Correlation vs. Causation
) R0 V# U( p8 b$ V' h, {9 W/ t474 - Fallacies
6 O' e/ Z" Q! G8 [475 - Intro to Linear Regression + q7 D1 f. h& }/ P; T9 g0 k
476 - Airplane Flights & {1 c4 r- S- w7 w, E' d3 m' X/ @
477 - Symbolize Regression Equation
6 o2 b" F" F1 q+ {% t478 - Symbolize Regression Equation Solution
# u9 t* B+ A( U# P% `479 - Guess Best Fit Line
7 ^; ^$ M( W, L- J( D/ h48 - CI Range for Larger Sample Size Solution ' q2 y& U( p& H# P |4 i
480 - Guess Best Fit Line Solution
) b3 F! { C$ } _8 t+ x481 - Minimize Sum of Squares - ?/ {' V! B- _! @% H3 B
482 - Calculate r % `4 \1 |/ O1 h: Y/ z5 w
483 - Calculate r Solution
2 P' U$ U( B1 u. E484 - Calculate Standard Deviations 7 ]. S( p- Y$ x* I$ u1 t
485 - Calculate Standard Deviations Solution
1 M0 `5 v* W$ M* A( U4 ]486 - Calculate Slope " y" I& d( ~/ k2 o8 j4 b% y& X( a
487 - Calculate Slope Solution
( Z& j4 |. {% J- v488 - Find y-Intercept
' q9 _" _3 r$ F) L9 @) {1 }489 - Find y-Intercept Solution " G; h0 b4 e5 t% w E
49 - CI When n = 250
6 B6 G& j/ I/ _3 o( z3 w/ W! M/ _9 A490 - What Point Does the Line Go Through_ 7 O" O# i8 p7 Y4 e
491 - What Point Does the Line Go Through_ Solution
- j& n% A$ i& d, z+ f* F" s6 d* C492 - Calculate Means
# L0 h# ]* e v; x0 f# b) c493 - Calculate Means Solution
. ~/ p3 b5 j2 X. w494 - Calculate y-Intercept
$ T2 }+ Q8 \" x7 B$ d! f495 - Calculate y-Intercept Solution 9 _( |& E" M3 V. v( K
496 - Travel 4000 Miles - y8 N7 q. W7 E, k
497 - Travel 4000 Miles Solution % T/ w5 d3 J! ~5 q" A+ e( L0 U
498 - Additional Cost per Mile
" j1 H: N: n% M0 P( B7 {499 - Additional Cost per Mile Solution / @- r! }# S: |/ y
5 - Klout Parameters Solution
4 }' [8 ?; r5 Z2 f# `6 q50 - CI When n = 250 Solution
. t( u9 L$ k- f# m1 i9 S500 - Cost to Travel 0 Miles
* L& u7 |" u; ~# x( p2 A1 W4 L501 - Cost to Travel 0 Miles Solution # C, v7 b- I4 e1 \# s. O
502 - Travel on a Budget
' y% P. [4 ]; G Q( I503 - Travel on a Budget Solution 0 s2 }8 P1 {( ?- ]
504 - Which Has More Error_ + M8 ]/ M9 s* n
505 - Which Has More Error_ Solution
6 j# J& _% U: x' L506 - Standard Error of Estimate
1 z; d+ R! A: _) b: W- J# J507 - Confidence Intervals a' S9 \$ }0 z& O
508 - Hypothesis Testing for Slope
+ r# q( @: v d( W y; q509 - Hypothesis Testing for Slope Solution - t2 g' a8 e. M6 q$ O
51 - Bigger Sample, Smaller CI ( a! Z* H8 W0 d5 a) F
510 - t-Test for Slope
3 K9 Q8 U0 z! ~9 k7 d9 }1 ^0 Z511 - t-Test for Slope Solution
1 g2 i$ Q, D* d1 j- N4 _+ y! p512 - R Output
r! [ N; @2 P0 @ U6 P4 j! O" `513 - Factors Affecting Linear Regression
) L0 K1 m7 m( K$ v! t514 - Summary of Linear Regression 4 e( N, Y1 T" Y# z
515 - Intro to Multiple Regression " i9 `+ j q6 S9 h. K1 A* K
516 - Alcohol, Religiosity, & Self-Esteem
! q5 I5 d, z+ Q517 - Alcohol, Religiosity, & Self-Esteem Solution
$ F( t9 [0 g8 _2 q518 - Make Predictions - g) U# H# d: b* e5 M/ M/ e
519 - Make Predictions Solution ; P- G4 ~. }' X w
52 - Z for 98% CI
4 D# W) l, t6 \1 K520 - Relationship
* j" `$ J l/ |) S' K521 - Relationship Solution % e% Q1 @% k, r. X
522 - Causation
" G6 e+ y, C! Y523 - Causation Solution
M: A" \9 k* g- b% T524 - Applets " Z6 T+ X- @- G! V6 ^% v+ e
525 - Scales of Measurement
7 _2 P/ y5 ^4 r526 - Scales of Measurement Solution
% }& Z# ^& `! u527 - Choose Type of Data
1 U) y. g0 }( Z: I! e' A& V& ]528 - Choose Type of Data Solution
2 |& g& o, L6 u$ t) ]* t/ j* [529 - Non-Parametric Tests
b4 M1 G- O: [% C- \. j53 - Z for 98% CI Solution : x. [) F) `/ j3 X4 O+ d
530 - Mount Shasta ( v/ q0 f$ I, J( B$ u6 n( O
531 - Mount Shasta Solution
2 I: Z- s, P( A532 - Expected Frequencies
0 j% G# d5 S7 s( w% k533 - Expected Frequencies Solution & K- k0 v' ~" {& L' J% f x
534 - Observed Frequency % ~3 h- A! w' B7 z/ X7 W; u/ x
535 - Observed Frequency Solution
* W g( M- Z7 p5 o7 }) x9 v6 S% }536 - Hypotheses Percent
2 f. V% D9 ~) j2 I& a537 - Hypotheses Percent Solution
3 B1 l/ |3 G( B5 S; r. h538 - Hypotheses Frequency
3 W+ X% N! ^+ M: D) T539 - Hypotheses Frequency Solution # U1 }' w& y+ g' D: p6 }
54 - Find 98% CI , ]# L- j3 H/ ^" a2 Q5 _/ U/ a* `
540 - Expected Frequencies 8 f/ J! T/ X9 b9 Z6 S
541 - Expected Frequencies Solution
3 N' ~% g+ C) }542 - χ^2 Goodness-of-Fit Test " v9 V. ?6 i8 C* V1 Q: [. O
543 - χ^2 Statistic 4 u- g5 B& a" l' h M6 e# v
544 - χ^2 Statistic Solution 2 |7 S) X% u- V
545 - Observed Equals Expected
) k7 ?" M4 Q! B/ ^546 - Observed Equals Expected Solution
$ O3 `* O- F' s6 d1 c4 T V3 `547 - χ^2 Values 6 ~: E! C6 Z% r4 V" y! s2 x: W& o3 x
548 - χ^2 Values Solution
3 l0 }0 w# ^; }# V) z549 - Degrees of Freedom : g# ^+ T8 s" K; P
55 - Find 98% CI Solution + j7 S7 H" a3 L9 d
550 - Degrees of Freedom Solution
+ z, B( t8 X/ K9 ?. B551 - Which Has More df_
7 z4 A. X4 \) K0 t: o552 - Which Has More df_ Solution ( l% l! x. v5 u T% @; }8 B4 |2 e
553 - Calculate χ^2 Statistic
& G. t8 Z; q7 s/ U554 - Calculate χ^2 Statistic Solution + N5 O- d/ H! Y4 q( W2 D
555 - Find df
' J' r( q9 H2 I+ k, h @$ T# T556 - Find df Solution
; ~5 Q( u0 `' `. l" g; v557 - Calculate p . t9 p# b) }: n. s+ s* \& Y! Z
558 - Calculate p Solution
3 H2 h* k7 u' e! o* f559 - χ^2 Test for Independence 9 w1 E7 g0 h3 |( t
56 - Critical Values of Z - Z5 G4 K; ?4 `* T# \0 G
560 - Remember Details : {% C% n+ L9 Y; L/ A' _: ^
561 - Remember Details Solution ! X$ l+ s% j5 i! I+ _# R% t8 T
562 - Broken Glass
% `5 _. L. v6 L- c563 - Broken Glass Solution 7 s$ U% T: e9 ^$ w4 F2 a
564 - Expected Frequencies
" X- p9 t3 C- l" _/ }$ a565 - Expected Frequencies Solution . J9 j* q) N3 _. s% D. ?
566 - Calculate χ^2 Statistic
) u; \5 d. P* l+ _- x& T' ^567 - Calculate χ^2 Statistic Solution
2 g# e3 U- L+ n5 ~) \6 A$ j; U568 - Degrees of Freedom
) ]2 m: U" t$ e6 [9 L569 - Degrees of Freedom Solution
5 }4 Q; L* F9 X) P4 O57 - Engagement Ratio 3 {" I. c! w/ h) D
570 - Decision ' }; D2 j* s9 g+ `5 D# p: Z
571 - Decision Solution 8 J, K2 x3 w9 K
572 - Effect Size
+ Q8 ]2 Q, [6 S! ]573 - Effect Size Solution 8 o4 P \) W3 F3 {: B
574 - Calculate Cramér's V 1 n( K0 T5 t3 c8 Y- T! Z
575 - Calculate Cramér's V Solution 9 d, f" R" e* p! s; I
576 - Assumptions and Restrictions # i* v( H' O' Z
577 - Summary ! |! X' Y! T+ i4 b( M
578 - Congrats + A: H9 [7 S" Q9 I9 f( D3 O
579 - Lauren's Outro Video
8 W, a0 T# c5 l8 T4 A/ { u58 - Engagement Ratio Solution
. J: o/ I5 u% [% C580 - Tutorial
0 G; n; d) Q2 N8 R% L3 {' v% o59 - Hypothesis Testing Song
, ?! S0 i9 D/ {/ y4 J3 Z6 - Klout Sampling Distribution (Mean)
8 v0 B( n( x1 t' e1 J60 - Point Estimate Engagement Ratio
2 d: K. X& }- v' }5 k$ _# g& w( j& ]9 R61 - Point Estimate Engagement Ratio Solution
1 Q7 p1 Q/ W7 M: v7 @# C' M62 - Standard Error
7 z# M* [4 z0 B1 _2 i) V3 q0 s63 - Standard Error Solution
6 a# l. s# i* J8 ~5 l9 I64 - CI Bounds
6 x' b8 S& i9 E# H, |65 - CI Bounds Solution 4 d `1 }# p* c
66 - Generalize CI + m( M* X Q7 a) T. A3 q2 l
67 - Generalize CI Solution
; d5 F7 G( z) [# C9 P) F68 - Margin of Error
. M! N* D4 s! F% Y4 f69 - Rate Engagement and Learning : J" j3 r& ?; v e( B. ?" l
7 - Klout Sampling Distribution (Mean) Solution 5 J4 q, F9 ^9 B( c# I6 l0 X
70 - Rate Engagement and Learning Solution ' i" h: ^8 c: D) R8 c8 c
71 - Results from Sample
! h# ~% w' b2 T# y7 B72 - What Statistics_ . a/ {8 l" q. \, F% U
73 - What Statistics_ Solution , g3 l/ Q2 c2 D" H0 m$ y
74 - Sampling Distributions 5 z* E9 `2 M7 Y% _& o# G
75 - Sampling Distributions Solution 2 {% Y' Q% n. ?
76 - Z-Scores of Sample Means 7 d H G* i. z
77 - Z-Scores of Sample Means Solution
) l4 U. e# E+ h/ Y% Z* f78 - Probability Sample Mean Is at Least...
$ \: O6 K8 b* w! a6 x, ?4 _9 }' Z* L79 - Probability Sample Mean Is at Least... Solution
5 H; n) d4 e6 o5 C) v8 - Klout Sampling Distribution (SD)
, w# B+ ]- a& \( x80 - What Does This Mean_
% A' h- W. E7 R; J. E81 - What Does This Mean_ Solution
9 U- w: L: ^, s2 I82 - Wrap-Up 9 Q' D9 j- | l i7 k8 M" R
83 - Likely or Unlikely 7 ?" v, d2 ?# _
84 - Likely or Unlikely Solution
: J- J; u( g4 M2 @- @& ^5 `7 D85 - Alpha Levels
9 Q; p, |$ `/ U+ r) F) w8 _- T, x( r86 - Alpha Levels Solution
2 q- L8 Y: Q; E* h6 {# U$ t87 - Z-Critical Value 0.05 ) q j6 C8 V! c3 \, R! J7 t
88 - Z-Critical Value 0.05 Solution 1 ~9 Q+ _. z5 f
89 - Critical Values 0.01 ! m R' p8 `' V7 Z) ?& P7 {
9 - Klout Sampling Distribution (SD) Solution
- e- Q# {! I+ G( ?/ @90 - Critical Values 0.01 Solution
j7 N0 K' C% _9 s& n. ]5 M+ p91 - Critical Values 0.001
) [/ D" o z d- r" z2 s$ n92 - Critical Values 0.001 Solution
; Z! j ]5 ~: e' P- N% T5 U93 - Critical Regions 5 E* ^6 Z3 d3 ]' e9 Q4 r
94 - Significance
" N( d$ a/ q% O) y6 `# y95 - Significance Solution ) k0 O. ~2 o/ g+ Z' u. D- s; x- G
96 - Darts 9 K2 ?- A8 h" I( _0 R7 d: c9 Z* r
97 - Z-Score 9 D$ D# s6 T, B& b# n/ e4 ^( W- W
98 - Z-Score Solution + b1 ]" b. ]- H: K7 Y
99 - Two-Tailed Critical Values 0.05 ) K5 X( k( F8 ?1 J
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发表于 2022-6-23 19:54:02
